Operations on Arrays

AbsDiff

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void cvAbsDiff(const CvArr* src1, const CvArr* src2, CvArr* dst)

Calculates absolute difference between two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array

The function calculates absolute difference between two arrays.

All the arrays must have the same data type and the same size (or ROI size).

AbsDiffS

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void cvAbsDiffS(const CvArr* src, CvArr* dst, CvScalar value)

Calculates absolute difference between an array and a scalar.

#define cvAbs(src, dst) cvAbsDiffS(src, dst, cvScalarAll(0))

param src:The source array param dst:The destination array param value:The scalar

The function calculates absolute difference between an array and a scalar.

All the arrays must have the same data type and the same size (or ROI size).

Add

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void cvAdd(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL)

Computes the per-element sum of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function adds one array to another:

dst(I)=src1(I)+src2(I) if mask(I)!=0

All the arrays must have the same type, except the mask, and the same size (or ROI size). For types that have limited range this operation is saturating.

AddS

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void cvAddS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)

Computes the sum of an array and a scalar.

Parameters:

• src – The source array
• value – Added scalar
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function adds a scalar value to every element in the source array src1 and stores the result in dst . For types that have limited range this operation is saturating.

dst(I)=src(I)+value if mask(I)!=0

All the arrays must have the same type, except the mask, and the same size (or ROI size).

AddWeighted

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void cvAddWeighted(const CvArr* src1, double alpha, const CvArr* src2, double beta, double gamma, CvArr* dst)

Computes the weighted sum of two arrays.

Parameters:

• src1 – The first source array
• alpha – Weight for the first array elements
• src2 – The second source array
• beta – Weight for the second array elements
• dst – The destination array
• gamma – Scalar, added to each sum

The function calculates the weighted sum of two arrays as follows:

dst(I)=src1(I)*alpha+src2(I)*beta+gamma

All the arrays must have the same type and the same size (or ROI size). For types that have limited range this operation is saturating.

And

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void cvAnd(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL)

Calculates per-element bit-wise conjunction of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function calculates per-element bit-wise logical conjunction of two arrays:

dst(I)=src1(I)&src2(I) if mask(I)!=0

In the case of floating-point arrays their bit representations are used for the operation. All the arrays must have the same type, except the mask, and the same size.

AndS

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void cvAndS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)

Calculates per-element bit-wise conjunction of an array and a scalar.

Parameters:

• src – The source array
• value – Scalar to use in the operation
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function calculates per-element bit-wise conjunction of an array and a scalar:

dst(I)=src(I)&value if mask(I)!=0

Prior to the actual operation, the scalar is converted to the same type as that of the array(s). In the case of floating-point arrays their bit representations are used for the operation. All the arrays must have the same type, except the mask, and the same size.

The following sample demonstrates how to calculate the absolute value of floating-point array elements by clearing the most-significant bit:

float a[] = { -1, 2, -3, 4, -5, 6, -7, 8, -9 };
CvMat A = cvMat(3, 3, CV_32F, &a);
int i, absMask = 0x7fffffff;
cvAndS(&A, cvRealScalar(*(float*)&absMask), &A, 0);
for(i = 0; i < 9; i++ )
    printf("

The code should print:

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0

Avg

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CvScalar cvAvg(const CvArr* arr, const CvArr* mask=NULL)

Calculates average (mean) of array elements.

Parameters:

• arr – The array
• mask – The optional operation mask

The function calculates the average value M of array elements, independently for each channel:

If the array is IplImage and COI is set, the function processes the selected channel only and stores the average to the first scalar component .

AvgSdv

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void cvAvgSdv(const CvArr* arr, CvScalar* mean, CvScalar* stdDev, const CvArr* mask=NULL)

Calculates average (mean) of array elements.

Parameters:

• arr – The array
• mean – Pointer to the output mean value, may be NULL if it is not needed
• stdDev – Pointer to the output standard deviation
• mask – The optional operation mask

The function calculates the average value and standard deviation of array elements, independently for each channel:

If the array is IplImage and COI is set, the function processes the selected channel only and stores the average and standard deviation to the first components of the output scalars ( and ).

CalcCovarMatrix

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void cvCalcCovarMatrix(const CvArr** vects, int count, CvArr* covMat, CvArr* avg, int flags)

Calculates covariance matrix of a set of vectors.

Parameters:

• vects – The input vectors, all of which must have the same type and the same size. The vectors do not have to be 1D, they can be 2D (e.g., images) and so forth
• count – The number of input vectors
• covMat – The output covariance matrix that should be floating-point and square
• avg – The input or output (depending on the flags) array - the mean (average) vector of the input vectors
• flags –

  The operation flags, a combination of the following values

  • CV_COVAR_SCRAMBLED The output covariance matrix is calculated as:

    

    , that is, the covariance matrix is . Such an unusual covariance matrix is used for fast PCA of a set of very large vectors (see, for example, the EigenFaces technique for face recognition). Eigenvalues of this “scrambled” matrix will match the eigenvalues of the true covariance matrix and the “true” eigenvectors can be easily calculated from the eigenvectors of the “scrambled” covariance matrix.

  • CV_COVAR_NORMAL The output covariance matrix is calculated as:

    

    , that is, covMat will be a covariance matrix with the same linear size as the total number of elements in each input vector. One and only one of CV_COVAR_SCRAMBLED and CV_COVAR_NORMAL must be specified

  • CV_COVAR_USE_AVG If the flag is specified, the function does not calculate avg from the input vectors, but, instead, uses the passed avg vector. This is useful if avg has been already calculated somehow, or if the covariance matrix is calculated by parts - in this case, avg is not a mean vector of the input sub-set of vectors, but rather the mean vector of the whole set.
  • CV_COVAR_SCALE If the flag is specified, the covariance matrix is scaled. In the “normal” mode scale is ‘1./count’; in the “scrambled” mode scale is the reciprocal of the total number of elements in each input vector. By default (if the flag is not specified) the covariance matrix is not scaled (‘scale=1’).
  • CV_COVAR_ROWS Means that all the input vectors are stored as rows of a single matrix, vects[0] . count is ignored in this case, and avg should be a single-row vector of an appropriate size.
  • CV_COVAR_COLS Means that all the input vectors are stored as columns of a single matrix, vects[0] . count is ignored in this case, and avg should be a single-column vector of an appropriate size.

The function calculates the covariance matrix and, optionally, the mean vector of the set of input vectors. The function can be used for PCA, for comparing vectors using Mahalanobis distance and so forth.

CartToPolar

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void cvCartToPolar(const CvArr* x, const CvArr* y, CvArr* magnitude, CvArr* angle=NULL, int angleInDegrees=0)

Calculates the magnitude and/or angle of 2d vectors.

Parameters:

• x – The array of x-coordinates
• y – The array of y-coordinates
• magnitude – The destination array of magnitudes, may be set to NULL if it is not needed
• angle – The destination array of angles, may be set to NULL if it is not needed. The angles are measured in radians to or in degrees (0 to 360 degrees).
• angleInDegrees – The flag indicating whether the angles are measured in radians, which is default mode, or in degrees

The function calculates either the magnitude, angle, or both of every 2d vector (x(I),y(I)):

magnitude(I)=sqrt(x(I)^2^+y(I)^2^ ),
angle(I)=atan(y(I)/x(I) )

The angles are calculated with 0.1 degree accuracy. For the (0,0) point, the angle is set to 0.

Cbrt

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float cvCbrt(float value)

Calculates the cubic root

Parameters:

• value – The input floating-point value

The function calculates the cubic root of the argument, and normally it is faster than pow(value,1./3) . In addition, negative arguments are handled properly. Special values ( , NaN) are not handled.

ClearND

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void cvClearND(CvArr* arr, int* idx)

Clears a specific array element.

Parameters:

• arr – Input array
• idx – Array of the element indices

The function ClearND clears (sets to zero) a specific element of a dense array or deletes the element of a sparse array. If the sparse array element does not exists, the function does nothing.

CloneImage

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IplImage* cvCloneImage(const IplImage* image)

Makes a full copy of an image, including the header, data, and ROI.

Parameters:

• image – The original image

The returned IplImage* points to the image copy.

CloneMat

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CvMat* cvCloneMat(const CvMat* mat)

Creates a full matrix copy.

Parameters:

• mat – Matrix to be copied

Creates a full copy of a matrix and returns a pointer to the copy.

CloneMatND

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CvMatND* cvCloneMatND(const CvMatND* mat)

Creates full copy of a multi-dimensional array and returns a pointer to the copy.

Parameters:

• mat – Input array

CloneSparseMat

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CvSparseMat* cvCloneSparseMat(const CvSparseMat* mat)

Creates full copy of sparse array.

Parameters:

• mat – Input array

The function creates a copy of the input array and returns pointer to the copy.

Cmp

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void cvCmp(const CvArr* src1, const CvArr* src2, CvArr* dst, int cmpOp)

Performs per-element comparison of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array. Both source arrays must have a single channel.
• dst – The destination array, must have 8u or 8s type
• cmpOp –

  The flag specifying the relation between the elements to be checked

  • CV_CMP_EQ src1(I) “equal to” value
  • CV_CMP_GT src1(I) “greater than” value
  • CV_CMP_GE src1(I) “greater or equal” value
  • CV_CMP_LT src1(I) “less than” value
  • CV_CMP_LE src1(I) “less or equal” value
  • CV_CMP_NE src1(I) “not equal” value

The function compares the corresponding elements of two arrays and fills the destination mask array:

dst(I)=src1(I) op src2(I),

dst(I) is set to 0xff (all 1 -bits) if the specific relation between the elements is true and 0 otherwise. All the arrays must have the same type, except the destination, and the same size (or ROI size)

CmpS

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void cvCmpS(const CvArr* src, double value, CvArr* dst, int cmpOp)

Performs per-element comparison of an array and a scalar.

Parameters:

• src – The source array, must have a single channel
• value – The scalar value to compare each array element with
• dst – The destination array, must have 8u or 8s type
• cmpOp –

  The flag specifying the relation between the elements to be checked

  • CV_CMP_EQ src1(I) “equal to” value
  • CV_CMP_GT src1(I) “greater than” value
  • CV_CMP_GE src1(I) “greater or equal” value
  • CV_CMP_LT src1(I) “less than” value
  • CV_CMP_LE src1(I) “less or equal” value
  • CV_CMP_NE src1(I) “not equal” value

The function compares the corresponding elements of an array and a scalar and fills the destination mask array:

dst(I)=src(I) op scalar

where op is .

dst(I) is set to 0xff (all 1 -bits) if the specific relation between the elements is true and 0 otherwise. All the arrays must have the same size (or ROI size).

ConvertScale

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void cvConvertScale(const CvArr* src, CvArr* dst, double scale=1, double shift=0)

Converts one array to another with optional linear transformation.

#define cvCvtScale cvConvertScale
#define cvScale  cvConvertScale
#define cvConvert(src, dst )  cvConvertScale((src), (dst), 1, 0 )

param src:Source array param dst:Destination array param scale:Scale factor param shift:Value added to the scaled source array elements

The function has several different purposes, and thus has several different names. It copies one array to another with optional scaling, which is performed first, and/or optional type conversion, performed after:

All the channels of multi-channel arrays are processed independently.

The type of conversion is done with rounding and saturation, that is if the result of scaling + conversion can not be represented exactly by a value of the destination array element type, it is set to the nearest representable value on the real axis.

In the case of scale=1, shift=0 no prescaling is done. This is a specially optimized case and it has the appropriate Convert name. If source and destination array types have equal types, this is also a special case that can be used to scale and shift a matrix or an image and that is caled Scale .

ConvertScaleAbs

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void cvConvertScaleAbs(const CvArr* src, CvArr* dst, double scale=1, double shift=0)

Converts input array elements to another 8-bit unsigned integer with optional linear transformation.

Parameters:

• src – Source array
• dst – Destination array (should have 8u depth)
• scale – ScaleAbs factor
• shift – Value added to the scaled source array elements

The function is similar to ConvertScale , but it stores absolute values of the conversion results:

The function supports only destination arrays of 8u (8-bit unsigned integers) type; for other types the function can be emulated by a combination of ConvertScale and Abs functions.

CvtScaleAbs

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void cvCvtScaleAbs(const CvArr* src, CvArr* dst, double scale=1, double shift=0)

Converts input array elements to another 8-bit unsigned integer with optional linear transformation.

Parameters:

• src – Source array
• dst – Destination array (should have 8u depth)
• scale – ScaleAbs factor
• shift – Value added to the scaled source array elements

The function is similar to ConvertScale , but it stores absolute values of the conversion results:

The function supports only destination arrays of 8u (8-bit unsigned integers) type; for other types the function can be emulated by a combination of ConvertScale and Abs functions.

Copy

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void cvCopy(const CvArr* src, CvArr* dst, const CvArr* mask=NULL)

Copies one array to another.

Parameters:

• src – The source array
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function copies selected elements from an input array to an output array:

If any of the passed arrays is of IplImage type, then its ROI and COI fields are used. Both arrays must have the same type, the same number of dimensions, and the same size. The function can also copy sparse arrays (mask is not supported in this case).

CountNonZero

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int cvCountNonZero(const CvArr* arr)

Counts non-zero array elements.

Parameters:

• arr – The array must be a single-channel array or a multi-channel image with COI set

The function returns the number of non-zero elements in arr:

In the case of IplImage both ROI and COI are supported.

CreateData

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void cvCreateData(CvArr* arr)

Allocates array data

Parameters:

• arr – Array header

The function allocates image, matrix or multi-dimensional array data. Note that in the case of matrix types OpenCV allocation functions are used and in the case of IplImage they are used unless CV_TURN_ON_IPL_COMPATIBILITY was called. In the latter case IPL functions are used to allocate the data.

CreateImage

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IplImage* cvCreateImage(CvSize size, int depth, int channels)

Creates an image header and allocates the image data.

Parameters:

• size – Image width and height
• depth – Bit depth of image elements. See IplImage for valid depths.
• channels – Number of channels per pixel. See IplImage for details. This function only creates images with interleaved channels.

This call is a shortened form of

header = cvCreateImageHeader(size, depth, channels);
cvCreateData(header);

CreateImageHeader

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IplImage* cvCreateImageHeader(CvSize size, int depth, int channels)

Creates an image header but does not allocate the image data.

Parameters:

• size – Image width and height
• depth – Image depth (see CreateImage )
• channels – Number of channels (see CreateImage )

This call is an analogue of

hdr=iplCreateImageHeader(channels, 0, depth,
                      channels == 1 ? "GRAY" : "RGB",
                      channels == 1 ? "GRAY" : channels == 3 ? "BGR" :
                      channels == 4 ? "BGRA" : "",
                      IPL_DATA_ORDER_PIXEL, IPL_ORIGIN_TL, 4,
                      size.width, size.height,
                      0,0,0,0);

but it does not use IPL functions by default (see the CV_TURN_ON_IPL_COMPATIBILITY macro).

CreateMat

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CvMat* cvCreateMat(int rows, int cols, int type)

Creates a matrix header and allocates the matrix data.

Parameters:

• rows – Number of rows in the matrix
• cols – Number of columns in the matrix
• type – The type of the matrix elements in the form CV_<bit depth><S|U|F>C<number of channels> , where S=signed, U=unsigned, F=float. For example, CV _ 8UC1 means the elements are 8-bit unsigned and the there is 1 channel, and CV _ 32SC2 means the elements are 32-bit signed and there are 2 channels.

This is the concise form for:

CvMat* mat = cvCreateMatHeader(rows, cols, type);
cvCreateData(mat);

CreateMatHeader

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CvMat* cvCreateMatHeader(int rows, int cols, int type)

Creates a matrix header but does not allocate the matrix data.

Parameters:

• rows – Number of rows in the matrix
• cols – Number of columns in the matrix
• type – Type of the matrix elements, see CreateMat

The function allocates a new matrix header and returns a pointer to it. The matrix data can then be allocated using CreateData or set explicitly to user-allocated data via SetData .

CreateMatND

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CvMatND* cvCreateMatND(int dims, const int* sizes, int type)

Creates the header and allocates the data for a multi-dimensional dense array.

Parameters:

• dims – Number of array dimensions. This must not exceed CV _ MAX _ DIM (32 by default, but can be changed at build time).
• sizes – Array of dimension sizes.
• type – Type of array elements, see CreateMat .

This is a short form for:

CvMatND* mat = cvCreateMatNDHeader(dims, sizes, type);
cvCreateData(mat);

CreateMatNDHeader

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CvMatND* cvCreateMatNDHeader(int dims, const int* sizes, int type)

Creates a new matrix header but does not allocate the matrix data.

Parameters:

• dims – Number of array dimensions
• sizes – Array of dimension sizes
• type – Type of array elements, see CreateMat

The function allocates a header for a multi-dimensional dense array. The array data can further be allocated using CreateData or set explicitly to user-allocated data via SetData .

CreateSparseMat

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CvSparseMat* cvCreateSparseMat(int dims, const int* sizes, int type)

Creates sparse array.

Parameters:

• dims – Number of array dimensions. In contrast to the dense matrix, the number of dimensions is practically unlimited (up to ).
• sizes – Array of dimension sizes
• type – Type of array elements. The same as for CvMat

The function allocates a multi-dimensional sparse array. Initially the array contain no elements, that is Get or GetReal returns zero for every index.

CrossProduct

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void cvCrossProduct(const CvArr* src1, const CvArr* src2, CvArr* dst)

Calculates the cross product of two 3D vectors.

Parameters:

• src1 – The first source vector
• src2 – The second source vector
• dst – The destination vector

The function calculates the cross product of two 3D vectors:

or:

CvtPixToPlane

Synonym for Split .

DCT

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void cvDCT(const CvArr* src, CvArr* dst, int flags)

Performs a forward or inverse Discrete Cosine transform of a 1D or 2D floating-point array.

Parameters:

• src – Source array, real 1D or 2D array
• dst – Destination array of the same size and same type as the source
• flags –

  Transformation flags, a combination of the following values

  • CV_DXT_FORWARD do a forward 1D or 2D transform.
  • CV_DXT_INVERSE do an inverse 1D or 2D transform.
  • CV_DXT_ROWS do a forward or inverse transform of every individual row of the input matrix. This flag allows user to transform multiple vectors simultaneously and can be used to decrease the overhead (which is sometimes several times larger than the processing itself), to do 3D and higher-dimensional transforms and so forth.

The function performs a forward or inverse transform of a 1D or 2D floating-point array:

Forward Cosine transform of 1D vector of elements:

where

and , for .

Inverse Cosine transform of 1D vector of N elements:

(since is orthogonal matrix, )

Forward Cosine transform of 2D matrix:

Inverse Cosine transform of 2D vector of elements:

DFT

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void cvDFT(const CvArr* src, CvArr* dst, int flags, int nonzeroRows=0)

Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.

Parameters:

• src – Source array, real or complex
• dst – Destination array of the same size and same type as the source
• flags –

  Transformation flags, a combination of the following values

  • CV_DXT_FORWARD do a forward 1D or 2D transform. The result is not scaled.
  • CV_DXT_INVERSE do an inverse 1D or 2D transform. The result is not scaled. CV_DXT_FORWARD and CV_DXT_INVERSE are mutually exclusive, of course.
  • CV_DXT_SCALE scale the result: divide it by the number of array elements. Usually, it is combined with CV_DXT_INVERSE , and one may use a shortcut CV_DXT_INV_SCALE .
  • CV_DXT_ROWS do a forward or inverse transform of every individual row of the input matrix. This flag allows the user to transform multiple vectors simultaneously and can be used to decrease the overhead (which is sometimes several times larger than the processing itself), to do 3D and higher-dimensional transforms and so forth.
  • CV_DXT_INVERSE_SCALE same as CV_DXT_INVERSE + CV_DXT_SCALE
• nonzeroRows – Number of nonzero rows in the source array (in the case of a forward 2d transform), or a number of rows of interest in the destination array (in the case of an inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing via DFT. See the example below.

The function performs a forward or inverse transform of a 1D or 2D floating-point array:

Forward Fourier transform of 1D vector of N elements:

,

Inverse Fourier transform of 1D vector of N elements:

Forward Fourier transform of 2D vector of M N elements:

Inverse Fourier transform of 2D vector of M N elements:

In the case of real (single-channel) data, the packed format, borrowed from IPL, is used to represent the result of a forward Fourier transform or input for an inverse Fourier transform:

Note: the last column is present if N is even, the last row is present if M is even. In the case of 1D real transform the result looks like the first row of the above matrix.

Here is the example of how to compute 2D convolution using DFT.

CvMat* A = cvCreateMat(M1, N1, CVg32F);
CvMat* B = cvCreateMat(M2, N2, A->type);

// it is also possible to have only abs(M2-M1)+1 times abs(N2-N1)+1
// part of the full convolution result
CvMat* conv = cvCreateMat(A->rows + B->rows - 1, A->cols + B->cols - 1,
                           A->type);

// initialize A and B
...

int dftgM = cvGetOptimalDFTSize(A->rows + B->rows - 1);
int dftgN = cvGetOptimalDFTSize(A->cols + B->cols - 1);

CvMat* dftgA = cvCreateMat(dft_M, dft_N, A->type);
CvMat* dftgB = cvCreateMat(dft_M, dft_N, B->type);
CvMat tmp;

// copy A to dftgA and pad dft_A with zeros
cvGetSubRect(dftgA, &tmp, cvRect(0,0,A->cols,A->rows));
cvCopy(A, &tmp);
cvGetSubRect(dftgA, &tmp, cvRect(A->cols,0,dft_A->cols - A->cols,A->rows));
cvZero(&tmp);
// no need to pad bottom part of dftgA with zeros because of
// use nonzerogrows parameter in cvDFT() call below

cvDFT(dftgA, dft_A, CV_DXT_FORWARD, A->rows);

// repeat the same with the second array
cvGetSubRect(dftgB, &tmp, cvRect(0,0,B->cols,B->rows));
cvCopy(B, &tmp);
cvGetSubRect(dftgB, &tmp, cvRect(B->cols,0,dft_B->cols - B->cols,B->rows));
cvZero(&tmp);
// no need to pad bottom part of dftgB with zeros because of
// use nonzerogrows parameter in cvDFT() call below

cvDFT(dftgB, dft_B, CV_DXT_FORWARD, B->rows);

cvMulSpectrums(dftgA, dft_B, dft_A, 0 /* or CV_DXT_MUL_CONJ to get
                correlation rather than convolution */);

cvDFT(dftgA, dft_A, CV_DXT_INV_SCALE, conv->rows); // calculate only
                                                         // the top part
cvGetSubRect(dftgA, &tmp, cvRect(0,0,conv->cols,conv->rows));

cvCopy(&tmp, conv);

DecRefData

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void cvDecRefData(CvArr* arr)

Decrements an array data reference counter.

Parameters:

• arr – Pointer to an array header

The function decrements the data reference counter in a CvMat or CvMatND if the reference counter pointer is not NULL. If the counter reaches zero, the data is deallocated. In the current implementation the reference counter is not NULL only if the data was allocated using the CreateData function. The counter will be NULL in other cases such as: external data was assigned to the header using SetData , the matrix header is part of a larger matrix or image, or the header was converted from an image or n-dimensional matrix header.

Det

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double cvDet(const CvArr* mat)

Returns the determinant of a matrix.

Parameters:

• mat – The source matrix

The function returns the determinant of the square matrix mat . The direct method is used for small matrices and Gaussian elimination is used for larger matrices. For symmetric positive-determined matrices, it is also possible to run SVD with and then calculate the determinant as a product of the diagonal elements of .

Div

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void cvDiv(const CvArr* src1, const CvArr* src2, CvArr* dst, double scale=1)

Performs per-element division of two arrays.

Parameters:

• src1 – The first source array. If the pointer is NULL, the array is assumed to be all 1’s.
• src2 – The second source array
• dst – The destination array
• scale – Optional scale factor

The function divides one array by another:

All the arrays must have the same type and the same size (or ROI size).

DotProduct

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double cvDotProduct(const CvArr* src1, const CvArr* src2)

Calculates the dot product of two arrays in Euclidian metrics.

Parameters:

• src1 – The first source array
• src2 – The second source array

The function calculates and returns the Euclidean dot product of two arrays.

In the case of multiple channel arrays, the results for all channels are accumulated. In particular, cvDotProduct(a,a) where a is a complex vector, will return . The function can process multi-dimensional arrays, row by row, layer by layer, and so on.

EigenVV

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void cvEigenVV(CvArr* mat, CvArr* evects, CvArr* evals, double eps=0, int lowindex = -1, int highindex = -1)

Computes eigenvalues and eigenvectors of a symmetric matrix.

Parameters:

• mat – The input symmetric square matrix, modified during the processing
• evects – The output matrix of eigenvectors, stored as subsequent rows
• evals – The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is syncronized, of course)
• eps – Accuracy of diagonalization. Typically, DBL_EPSILON (about ) works well. THIS PARAMETER IS CURRENTLY IGNORED.
• lowindex – Optional index of largest eigenvalue/-vector to calculate. (See below.)
• highindex – Optional index of smallest eigenvalue/-vector to calculate. (See below.)

The function computes the eigenvalues and eigenvectors of matrix A :

mat*evects(i,:)' = evals(i)*evects(i,:)' (in MATLAB notation)

If either low- or highindex is supplied the other is required, too. Indexing is 0-based. Example: To calculate the largest eigenvector/-value set lowindex=highindex=0 . To calculate all the eigenvalues, leave lowindex=highindex=-1 . For legacy reasons this function always returns a square matrix the same size as the source matrix with eigenvectors and a vector the length of the source matrix with eigenvalues. The selected eigenvectors/-values are always in the first highindex - lowindex + 1 rows.

The contents of matrix A is destroyed by the function.

Currently the function is slower than SVD yet less accurate, so if A is known to be positively-defined (for example, it is a covariance matrix)it is recommended to use SVD to find eigenvalues and eigenvectors of A , especially if eigenvectors are not required.

Exp

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void cvExp(const CvArr* src, CvArr* dst)

Calculates the exponent of every array element.

Parameters:

• src – The source array
• dst – The destination array, it should have double type or the same type as the source

The function calculates the exponent of every element of the input array:

The maximum relative error is about . Currently, the function converts denormalized values to zeros on output.

FastArctan

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float cvFastArctan(float y, float x)

Calculates the angle of a 2D vector.

Parameters:

• x – x-coordinate of 2D vector
• y – y-coordinate of 2D vector

The function calculates the full-range angle of an input 2D vector. The angle is measured in degrees and varies from 0 degrees to 360 degrees. The accuracy is about 0.1 degrees.

Flip

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void cvFlip(const CvArr* src, CvArr* dst=NULL, int flipMode=0)

Flip a 2D array around vertical, horizontal or both axes.

Parameters:

• src – Source array
• dst – Destination array. If the flipping is done in place.
• flipMode – Specifies how to flip the array: 0 means flipping around the x-axis, positive (e.g., 1) means flipping around y-axis, and negative (e.g., -1) means flipping around both axes. See also the discussion below for the formulas:

The function flips the array in one of three different ways (row and column indices are 0-based):

The example scenarios of function use are:

• vertical flipping of the image (flipMode = 0) to switch between top-left and bottom-left image origin, which is a typical operation in video processing under Win32 systems.
• horizontal flipping of the image with subsequent horizontal shift and absolute difference calculation to check for a vertical-axis symmetry (flipMode 0)
• simultaneous horizontal and vertical flipping of the image with subsequent shift and absolute difference calculation to check for a central symmetry (flipMode 0)
• reversing the order of 1d point arrays (flipMode > 0)

GEMM

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void cvGEMM(const CvArr* src1, const CvArr* src2, double alpha, const CvArr* src3, double beta, CvArr* dst, int tABC=0)

#define cvMatMulAdd(src1, src2, src3, dst ) cvGEMM(src1, src2, 1, src3, 1, dst, 0 )#define cvMatMul(src1, src2, dst ) cvMatMulAdd(src1, src2, 0, dst)

Performs generalized matrix multiplication.

Parameters:

• src1 – The first source array
• src2 – The second source array
• src3 – The third source array (shift). Can be NULL, if there is no shift.
• dst – The destination array
• tABC –

  The operation flags that can be 0 or a combination of the following values

  • CV_GEMM_A_T transpose src1
  • CV_GEMM_B_T transpose src2
  • CV_GEMM_C_T transpose src3

  For example, CV_GEMM_A_T+CV_GEMM_C_T corresponds to

  

The function performs generalized matrix multiplication:

All the matrices should have the same data type and coordinated sizes. Real or complex floating-point matrices are supported.

Get?D

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CvScalar cvGet1D(const CvArr* arr, int idx0) CvScalar cvGet2D(const CvArr* arr, int idx0, int idx1) CvScalar cvGet3D(const CvArr* arr, int idx0, int idx1, int idx2) CvScalar cvGetND(const CvArr* arr, int* idx)

Return a specific array element.

Parameters:

• arr – Input array
• idx0 – The first zero-based component of the element index
• idx1 – The second zero-based component of the element index
• idx2 – The third zero-based component of the element index
• idx – Array of the element indices

The functions return a specific array element. In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).

GetCol(s)

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CvMat* cvGetCol(const CvArr* arr, CvMat* submat, int col)

Returns array column or column span.

CvMat* cvGetCols(const CvArr* arr, CvMat* submat, int startCol, int endCol)

Parameters:

• arr – Input array
• submat – Pointer to the resulting sub-array header
• col – Zero-based index of the selected column
• startCol – Zero-based index of the starting column (inclusive) of the span
• endCol – Zero-based index of the ending column (exclusive) of the span

The functions GetCol and GetCols return the header, corresponding to a specified column span of the input array. GetCol is a shortcut for GetCols :

cvGetCol(arr, submat, col); // ~ cvGetCols(arr, submat, col, col + 1);

GetDiag

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CvMat* cvGetDiag(const CvArr* arr, CvMat* submat, int diag=0)

Returns one of array diagonals.

Parameters:

• arr – Input array
• submat – Pointer to the resulting sub-array header
• diag – Array diagonal. Zero corresponds to the main diagonal, -1 corresponds to the diagonal above the main , 1 corresponds to the diagonal below the main, and so forth.

The function returns the header, corresponding to a specified diagonal of the input array.

cvGetDims, cvGetDimSize

Return number of array dimensions and their sizes or the size of a particular dimension.

int cvGetDims(const CvArr* arr, int* sizes=NULL)

int cvGetDimSize(const CvArr* arr, int index)

Parameters:

• arr – Input array
• sizes – Optional output vector of the array dimension sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next.
• index – Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width)

The function cvGetDims returns the array dimensionality and the array of dimension sizes. In the case of IplImage or CvMat it always returns 2 regardless of number of image/matrix rows. The function cvGetDimSize returns the particular dimension size (number of elements per that dimension). For example, the following code calculates total number of array elements in two ways:

// via cvGetDims()
int sizes[CV_MAX_DIM];
int i, total = 1;
int dims = cvGetDims(arr, size);
for(i = 0; i < dims; i++ )
    total *= sizes[i];

// via cvGetDims() and cvGetDimSize()
int i, total = 1;
int dims = cvGetDims(arr);
for(i = 0; i < dims; i++ )
    total *= cvGetDimsSize(arr, i);

GetElemType

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int cvGetElemType(const CvArr* arr)

Returns type of array elements.

Parameters:

• arr – Input array

The function returns type of the array elements as described in CreateMat discussion: CV_8UC1 ... CV_64FC4 .

GetImage

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IplImage* cvGetImage(const CvArr* arr, IplImage* imageHeader)

Returns image header for arbitrary array.

Parameters:

• arr – Input array
• imageHeader – Pointer to IplImage structure used as a temporary buffer

The function returns the image header for the input array that can be a matrix - CvMat , or an image - IplImage* . In the case of an image the function simply returns the input pointer. In the case of CvMat it initializes an imageHeader structure with the parameters of the input matrix. Note that if we transform IplImage to CvMat and then transform CvMat back to IplImage, we can get different headers if the ROI is set, and thus some IPL functions that calculate image stride from its width and align may fail on the resultant image.

GetImageCOI

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int cvGetImageCOI(const IplImage* image)

Returns the index of the channel of interest.

Parameters:

• image – A pointer to the image header

Returns the channel of interest of in an IplImage. Returned values correspond to the coi in SetImageCOI .

GetImageROI

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CvRect cvGetImageROI(const IplImage* image)

Returns the image ROI.

Parameters:

• image – A pointer to the image header

If there is no ROI set, cvRect(0,0,image->width,image->height) is returned.

GetMat

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CvMat* cvGetMat(const CvArr* arr, CvMat* header, int* coi=NULL, int allowND=0)

Returns matrix header for arbitrary array.

Parameters:

• arr – Input array
• header – Pointer to CvMat structure used as a temporary buffer
• coi – Optional output parameter for storing COI
• allowND – If non-zero, the function accepts multi-dimensional dense arrays (CvMatND*) and returns 2D (if CvMatND has two dimensions) or 1D matrix (when CvMatND has 1 dimension or more than 2 dimensions). The array must be continuous.

The function returns a matrix header for the input array that can be a matrix -

CvMat , an image - IplImage or a multi-dimensional dense array - CvMatND (latter case is allowed only if allowND != 0 ) . In the case of matrix the function simply returns the input pointer. In the case of IplImage* or CvMatND it initializes the header structure with parameters of the current image ROI and returns the pointer to this temporary structure. Because COI is not supported by CvMat , it is returned separately.

The function provides an easy way to handle both types of arrays - IplImage and CvMat - using the same code. Reverse transform from CvMat to IplImage can be done using the GetImage function.

Input array must have underlying data allocated or attached, otherwise the function fails.

If the input array is IplImage with planar data layout and COI set, the function returns the pointer to the selected plane and COI = 0. It enables per-plane processing of multi-channel images with planar data layout using OpenCV functions.

GetNextSparseNode

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CvSparseNode* cvGetNextSparseNode(CvSparseMatIterator* matIterator)

Returns the next sparse matrix element

Parameters:

• matIterator – Sparse array iterator

The function moves iterator to the next sparse matrix element and returns pointer to it. In the current version there is no any particular order of the elements, because they are stored in the hash table. The sample below demonstrates how to iterate through the sparse matrix:

Using InitSparseMatIterator and GetNextSparseNode to calculate sum of floating-point sparse array.

double sum;
int i, dims = cvGetDims(array);
CvSparseMatIterator mat_iterator;
CvSparseNode* node = cvInitSparseMatIterator(array, &mat_iterator);

for(; node != 0; node = cvGetNextSparseNode(&mat_iterator ))
{
    /* get pointer to the element indices */
    int* idx = CV_NODE_IDX(array, node);
    /* get value of the element (assume that the type is CV_32FC1) */
    float val = *(float*)CV_NODE_VAL(array, node);
    printf("(");
    for(i = 0; i < dims; i++ )
        printf("
    printf("

    sum += val;
}

printf("nTotal sum =

GetOptimalDFTSize

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int cvGetOptimalDFTSize(int size0)

Returns optimal DFT size for a given vector size.

Parameters:

• size0 – Vector size

The function returns the minimum number N that is greater than or equal to size0 , such that the DFT of a vector of size N can be computed fast. In the current implementation , for some , , .

The function returns a negative number if size0 is too large (very close to INT_MAX )

GetRawData

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void cvGetRawData(const CvArr* arr, uchar** data, int* step=NULL, CvSize* roiSize=NULL)

Retrieves low-level information about the array.

Parameters:

• arr – Array header
• data – Output pointer to the whole image origin or ROI origin if ROI is set
• step – Output full row length in bytes
• roiSize – Output ROI size

The function fills output variables with low-level information about the array data. All output parameters are optional, so some of the pointers may be set to NULL . If the array is IplImage with ROI set, the parameters of ROI are returned.

The following example shows how to get access to array elements. GetRawData calculates the absolute value of the elements in a single-channel, floating-point array.

float* data;
int step;

CvSize size;
int x, y;

cvGetRawData(array, (uchar**)&data, &step, &size);
step /= sizeof(data[0]);

for(y = 0; y < size.height; y++, data += step )
    for(x = 0; x < size.width; x++ )
        data[x] = (float)fabs(data[x]);

GetReal1D

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double cvGetReal1D(const CvArr* arr, int idx0)

Return a specific element of single-channel 1D array.

Parameters:

• arr – Input array. Must have a single channel.
• idx0 – The first zero-based component of the element index

Returns a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that Get function can be used safely for both single-channel and multiple-channel arrays though they are a bit slower.

In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).

GetReal2D

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double cvGetReal2D(const CvArr* arr, int idx0, int idx1)

Return a specific element of single-channel 2D array.

Parameters:

• arr – Input array. Must have a single channel.
• idx0 – The first zero-based component of the element index
• idx1 – The second zero-based component of the element index

Returns a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that Get function can be used safely for both single-channel and multiple-channel arrays though they are a bit slower.

In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).

GetReal3D

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double cvGetReal3D(const CvArr* arr, int idx0, int idx1, int idx2)

Return a specific element of single-channel array.

Parameters:

• arr – Input array. Must have a single channel.
• idx0 – The first zero-based component of the element index
• idx1 – The second zero-based component of the element index
• idx2 – The third zero-based component of the element index

Returns a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that Get function can be used safely for both single-channel and multiple-channel arrays though they are a bit slower.

In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).

GetRealND

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double cvGetRealND(const CvArr* arr, int* idx)->float

Return a specific element of single-channel array.

Parameters:

• arr – Input array. Must have a single channel.
• idx – Array of the element indices

Returns a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that Get function can be used safely for both single-channel and multiple-channel arrays though they are a bit slower.

In the case of a sparse array the functions return 0 if the requested node does not exist (no new node is created by the functions).

GetRow(s)

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CvMat* cvGetRow(const CvArr* arr, CvMat* submat, int row)

Returns array row or row span.

CvMat* cvGetRows(const CvArr* arr, CvMat* submat, int startRow, int endRow, int deltaRow=1)

Parameters:

• arr – Input array
• submat – Pointer to the resulting sub-array header
• row – Zero-based index of the selected row
• startRow – Zero-based index of the starting row (inclusive) of the span
• endRow – Zero-based index of the ending row (exclusive) of the span
• deltaRow – Index step in the row span. That is, the function extracts every deltaRow -th row from startRow and up to (but not including) endRow .

The functions return the header, corresponding to a specified row/row span of the input array. Note that GetRow is a shortcut for GetRows :

cvGetRow(arr, submat, row ) ~ cvGetRows(arr, submat, row, row + 1, 1);

GetSize

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CvSize cvGetSize(const CvArr* arr)

Returns size of matrix or image ROI.

Parameters:

• arr – array header

The function returns number of rows (CvSize::height) and number of columns (CvSize::width) of the input matrix or image. In the case of image the size of ROI is returned.

GetSubRect

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CvMat* cvGetSubRect(const CvArr* arr, CvMat* submat, CvRect rect)

Returns matrix header corresponding to the rectangular sub-array of input image or matrix.

Parameters:

• arr – Input array
• submat – Pointer to the resultant sub-array header
• rect – Zero-based coordinates of the rectangle of interest

The function returns header, corresponding to a specified rectangle of the input array. In other words, it allows the user to treat a rectangular part of input array as a stand-alone array. ROI is taken into account by the function so the sub-array of ROI is actually extracted.

InRange

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void cvInRange(const CvArr* src, const CvArr* lower, const CvArr* upper, CvArr* dst)

Checks that array elements lie between the elements of two other arrays.

Parameters:

• src – The first source array
• lower – The inclusive lower boundary array
• upper – The exclusive upper boundary array
• dst – The destination array, must have 8u or 8s type

The function does the range check for every element of the input array:

For single-channel arrays,

For two-channel arrays and so forth,

dst(I) is set to 0xff (all 1 -bits) if src(I) is within the range and 0 otherwise. All the arrays must have the same type, except the destination, and the same size (or ROI size).

InRangeS

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void cvInRangeS(const CvArr* src, CvScalar lower, CvScalar upper, CvArr* dst)

Checks that array elements lie between two scalars.

Parameters:

• src – The first source array
• lower – The inclusive lower boundary
• upper – The exclusive upper boundary
• dst – The destination array, must have 8u or 8s type

The function does the range check for every element of the input array:

For single-channel arrays,

For two-channel arrays nd so forth,

‘dst(I)’ is set to 0xff (all 1 -bits) if ‘src(I)’ is within the range and 0 otherwise. All the arrays must have the same size (or ROI size).

IncRefData

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int cvIncRefData(CvArr* arr)

Increments array data reference counter.

Parameters:

• arr – Array header

The function increments CvMat or CvMatND data reference counter and returns the new counter value if the reference counter pointer is not NULL, otherwise it returns zero.

InitImageHeader

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IplImage* cvInitImageHeader(IplImage* image, CvSize size, int depth, int channels, int origin=0, int align=4)

Initializes an image header that was previously allocated.

Parameters:

• image – Image header to initialize
• size – Image width and height
• depth – Image depth (see CreateImage )
• channels – Number of channels (see CreateImage )
• origin – Top-left IPL_ORIGIN_TL or bottom-left IPL_ORIGIN_BL
• align – Alignment for image rows, typically 4 or 8 bytes

The returned IplImage* points to the initialized header.

InitMatHeader

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CvMat* cvInitMatHeader(CvMat* mat, int rows, int cols, int type, void* data=NULL, int step=CV_AUTOSTEP)

Initializes a pre-allocated matrix header.

Parameters:

• mat – A pointer to the matrix header to be initialized
• rows – Number of rows in the matrix
• cols – Number of columns in the matrix
• type – Type of the matrix elements, see CreateMat .
• data – Optional: data pointer assigned to the matrix header
• step – Optional: full row width in bytes of the assigned data. By default, the minimal possible step is used which assumes there are no gaps between subsequent rows of the matrix.

This function is often used to process raw data with OpenCV matrix functions. For example, the following code computes the matrix product of two matrices, stored as ordinary arrays:

double a[] = { 1, 2, 3, 4,
               5, 6, 7, 8,
               9, 10, 11, 12 };

double b[] = { 1, 5, 9,
               2, 6, 10,
               3, 7, 11,
               4, 8, 12 };

double c[9];
CvMat Ma, Mb, Mc ;

cvInitMatHeader(&Ma, 3, 4, CV_64FC1, a);
cvInitMatHeader(&Mb, 4, 3, CV_64FC1, b);
cvInitMatHeader(&Mc, 3, 3, CV_64FC1, c);

cvMatMulAdd(&Ma, &Mb, 0, &Mc);
// the c array now contains the product of a (3x4) and b (4x3)

InitMatNDHeader

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CvMatND* cvInitMatNDHeader(CvMatND* mat, int dims, const int* sizes, int type, void* data=NULL)

Initializes a pre-allocated multi-dimensional array header.

Parameters:

• mat – A pointer to the array header to be initialized
• dims – The number of array dimensions
• sizes – An array of dimension sizes
• type – Type of array elements, see CreateMat
• data – Optional data pointer assigned to the matrix header

InitSparseMatIterator

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CvSparseNode* cvInitSparseMatIterator(const CvSparseMat* mat, CvSparseMatIterator* matIterator)

Initializes sparse array elements iterator.

Parameters:

• mat – Input array
• matIterator – Initialized iterator

The function initializes iterator of sparse array elements and returns pointer to the first element, or NULL if the array is empty.

InvSqrt

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float cvInvSqrt(float value)

Calculates the inverse square root.

Parameters:

• value – The input floating-point value

The function calculates the inverse square root of the argument, and normally it is faster than 1./sqrt(value) . If the argument is zero or negative, the result is not determined. Special values ( , NaN) are not handled.

Inv

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Invert

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double cvInvert(const CvArr* src, CvArr* dst, int method=CV_LU)

Finds the inverse or pseudo-inverse of a matrix.

Parameters:

• src – The source matrix
• dst – The destination matrix
• method –

  Inversion method

  • CV_LU Gaussian elimination with optimal pivot element chosen
  • CV_SVD Singular value decomposition (SVD) method
  • CV_SVD_SYM SVD method for a symmetric positively-defined matrix

The function inverts matrix src1 and stores the result in src2 .

In the case of LU method, the function returns the src1 determinant (src1 must be square). If it is 0, the matrix is not inverted and src2 is filled with zeros.

In the case of SVD methods, the function returns the inversed condition of src1 (ratio of the smallest singular value to the largest singular value) and 0 if src1 is all zeros. The SVD methods calculate a pseudo-inverse matrix if src1 is singular.

IsInf

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int cvIsInf(double value)

Determines if the argument is Infinity.

Parameters:

• value – The input floating-point value

The function returns 1 if the argument is (as defined by IEEE754 standard), 0 otherwise.

IsNaN

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int cvIsNaN(double value)

Determines if the argument is Not A Number.

Parameters:

• value – The input floating-point value

The function returns 1 if the argument is Not A Number (as defined by IEEE754 standard), 0 otherwise.

LUT

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void cvLUT(const CvArr* src, CvArr* dst, const CvArr* lut)

Performs a look-up table transform of an array.

Parameters:

• src – Source array of 8-bit elements
• dst – Destination array of a given depth and of the same number of channels as the source array
• lut – Look-up table of 256 elements; should have the same depth as the destination array. In the case of multi-channel source and destination arrays, the table should either have a single-channel (in this case the same table is used for all channels) or the same number of channels as the source/destination array.

The function fills the destination array with values from the look-up table. Indices of the entries are taken from the source array. That is, the function processes each element of src as follows:

where

Log

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void cvLog(const CvArr* src, CvArr* dst)

Calculates the natural logarithm of every array element’s absolute value.

Parameters:

• src – The source array
• dst – The destination array, it should have double type or the same type as the source

The function calculates the natural logarithm of the absolute value of every element of the input array:

Where C is a large negative number (about -700 in the current implementation).

Mahalanobis

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double cvMahalanobis(const CvArr* vec1, const CvArr* vec2, CvArr* mat)

Calculates the Mahalanobis distance between two vectors.

Parameters:

• vec1 – The first 1D source vector
• vec2 – The second 1D source vector
• mat – The inverse covariance matrix

The function calculates and returns the weighted distance between two vectors:

The covariance matrix may be calculated using the CalcCovarMatrix function and further inverted using the Invert function (CV _ SVD method is the prefered one because the matrix might be singular).

Mat

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CvMat cvMat(int rows, int cols, int type, void* data=NULL)

Initializes matrix header (lightweight variant).

Parameters:

• rows – Number of rows in the matrix
• cols – Number of columns in the matrix
• type – Type of the matrix elements - see CreateMat
• data – Optional data pointer assigned to the matrix header

Initializes a matrix header and assigns data to it. The matrix is filled row -wise (the first cols elements of data form the first row of the matrix, etc.)

This function is a fast inline substitution for InitMatHeader . Namely, it is equivalent to:

CvMat mat;
cvInitMatHeader(&mat, rows, cols, type, data, CV_AUTOSTEP);

Max

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void cvMax(const CvArr* src1, const CvArr* src2, CvArr* dst)

Finds per-element maximum of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array

The function calculates per-element maximum of two arrays:

All the arrays must have a single channel, the same data type and the same size (or ROI size).

MaxS

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void cvMaxS(const CvArr* src, double value, CvArr* dst)

Finds per-element maximum of array and scalar.

Parameters:

• src – The first source array
• value – The scalar value
• dst – The destination array

The function calculates per-element maximum of array and scalar:

All the arrays must have a single channel, the same data type and the same size (or ROI size).

Merge

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void cvMerge(const CvArr* src0, const CvArr* src1, const CvArr* src2, const CvArr* src3, CvArr* dst)

Composes a multi-channel array from several single-channel arrays or inserts a single channel into the array.

#define cvCvtPlaneToPix cvMerge

param src0:Input channel 0 param src1:Input channel 1 param src2:Input channel 2 param src3:Input channel 3 param dst:Destination array

The function is the opposite to Split . If the destination array has N channels then if the first N input channels are not NULL, they all are copied to the destination array; if only a single source channel of the first N is not NULL, this particular channel is copied into the destination array; otherwise an error is raised. The rest of the source channels (beyond the first N) must always be NULL. For IplImage Copy with COI set can be also used to insert a single channel into the image.

Min

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void cvMin(const CvArr* src1, const CvArr* src2, CvArr* dst)

Finds per-element minimum of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array

The function calculates per-element minimum of two arrays:

All the arrays must have a single channel, the same data type and the same size (or ROI size).

MinMaxLoc

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void cvMinMaxLoc(const CvArr* arr, double* minVal, double* maxVal, CvPoint* minLoc=NULL, CvPoint* maxLoc=NULL, const CvArr* mask=NULL)

Finds global minimum and maximum in array or subarray.

Parameters:

• arr – The source array, single-channel or multi-channel with COI set
• minVal – Pointer to returned minimum value
• maxVal – Pointer to returned maximum value
• minLoc – Pointer to returned minimum location
• maxLoc – Pointer to returned maximum location
• mask – The optional mask used to select a subarray

The function finds minimum and maximum element values and their positions. The extremums are searched across the whole array, selected ROI (in the case of IplImage ) or, if mask is not NULL , in the specified array region. If the array has more than one channel, it must be IplImage with COI set. In the case of multi-dimensional arrays, minLoc->x and maxLoc->x will contain raw (linear) positions of the extremums.

MinS

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void cvMinS(const CvArr* src, double value, CvArr* dst)

Finds per-element minimum of an array and a scalar.

Parameters:

• src – The first source array
• value – The scalar value
• dst – The destination array

The function calculates minimum of an array and a scalar:

All the arrays must have a single channel, the same data type and the same size (or ROI size).

Mirror

Synonym for Flip .

MixChannels

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void cvMixChannels(const CvArr** src, int srcCount, CvArr** dst, int dstCount, const int* fromTo, int pairCount)

Copies several channels from input arrays to certain channels of output arrays

Parameters:

• src – Input arrays
• srcCount – The number of input arrays.
• dst – Destination arrays
• dstCount – The number of output arrays.
• fromTo – The array of pairs of indices of the planes copied. fromTo[k*2] is the 0-based index of the input channel in src and fromTo[k*2+1] is the index of the output channel in dst . Here the continuous channel numbering is used, that is, the first input image channels are indexed from 0 to channels(src[0])-1 , the second input image channels are indexed from channels(src[0]) to channels(src[0]) + channels(src[1])-1 etc., and the same scheme is used for the output image channels. As a special case, when fromTo[k*2] is negative, the corresponding output channel is filled with zero.

The function is a generalized form of cvSplit and Merge and some forms of CvtColor . It can be used to change the order of the planes, add/remove alpha channel, extract or insert a single plane or multiple planes etc.

As an example, this code splits a 4-channel RGBA image into a 3-channel BGR (i.e. with R and B swapped) and separate alpha channel image:

CvMat* rgba = cvCreateMat(100, 100, CV_8UC4);
CvMat* bgr = cvCreateMat(rgba->rows, rgba->cols, CV_8UC3);
CvMat* alpha = cvCreateMat(rgba->rows, rgba->cols, CV_8UC1);
cvSet(rgba, cvScalar(1,2,3,4));

CvArr* out[] = { bgr, alpha };
int from_to[] = { 0,2,  1,1,  2,0,  3,3 };
cvMixChannels(&bgra, 1, out, 2, from_to, 4);

MulAddS

Synonym for ScaleAdd .

Mul

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void cvMul(const CvArr* src1, const CvArr* src2, CvArr* dst, double scale=1)

Calculates the per-element product of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array
• scale – Optional scale factor

The function calculates the per-element product of two arrays:

All the arrays must have the same type and the same size (or ROI size). For types that have limited range this operation is saturating.

MulSpectrums

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void cvMulSpectrums(const CvArr* src1, const CvArr* src2, CvArr* dst, int flags)

Performs per-element multiplication of two Fourier spectrums.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array of the same type and the same size as the source arrays
• flags –

  A combination of the following values;

  • CV_DXT_ROWS treats each row of the arrays as a separate spectrum (see DFT parameters description).
  • CV_DXT_MUL_CONJ conjugate the second source array before the multiplication.

The function performs per-element multiplication of the two CCS-packed or complex matrices that are results of a real or complex Fourier transform.

The function, together with DFT , may be used to calculate convolution of two arrays rapidly.

MulTransposed

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void cvMulTransposed(const CvArr* src, CvArr* dst, int order, const CvArr* delta=NULL, double scale=1.0)

Calculates the product of an array and a transposed array.

Parameters:

• src – The source matrix
• dst – The destination matrix. Must be CV_32F or CV_64F .
• order – Order of multipliers
• delta – An optional array, subtracted from src before multiplication
• scale – An optional scaling

The function calculates the product of src and its transposition:

if , and

otherwise.

Norm

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double cvNorm(const CvArr* arr1, const CvArr* arr2=NULL, int normType=CV_L2, const CvArr* mask=NULL)

Calculates absolute array norm, absolute difference norm, or relative difference norm.

Parameters:

• arr1 – The first source image
• arr2 – The second source image. If it is NULL, the absolute norm of arr1 is calculated, otherwise the absolute or relative norm of arr1 - arr2 is calculated.
• normType – Type of norm, see the discussion
• mask – The optional operation mask

The function calculates the absolute norm of arr1 if arr2 is NULL:

or the absolute difference norm if arr2 is not NULL:

or the relative difference norm if arr2 is not NULL and (normType & CV_RELATIVE) != 0 :

The function returns the calculated norm. A multiple-channel array is treated as a single-channel, that is, the results for all channels are combined.

Not

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void cvNot(const CvArr* src, CvArr* dst)

Performs per-element bit-wise inversion of array elements.

Parameters:

• src – The source array
• dst – The destination array

The function Not inverses every bit of every array element:

dst(I)=~src(I)

Or

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void cvOr(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL)

Calculates per-element bit-wise disjunction of two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function calculates per-element bit-wise disjunction of two arrays:

dst(I)=src1(I)|src2(I)

In the case of floating-point arrays their bit representations are used for the operation. All the arrays must have the same type, except the mask, and the same size.

OrS

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void cvOrS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)

Calculates a per-element bit-wise disjunction of an array and a scalar.

Parameters:

• src – The source array
• value – Scalar to use in the operation
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function OrS calculates per-element bit-wise disjunction of an array and a scalar:

dst(I)=src(I)|value if mask(I)!=0

Prior to the actual operation, the scalar is converted to the same type as that of the array(s). In the case of floating-point arrays their bit representations are used for the operation. All the arrays must have the same type, except the mask, and the same size.

PerspectiveTransform

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void cvPerspectiveTransform(const CvArr* src, CvArr* dst, const CvMat* mat)

Performs perspective matrix transformation of a vector array.

Parameters:

• src – The source three-channel floating-point array
• dst – The destination three-channel floating-point array
• mat – or transformation matrix

The function transforms every element of src (by treating it as 2D or 3D vector) in the following way:

where

and

PolarToCart

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void cvPolarToCart(const CvArr* magnitude, const CvArr* angle, CvArr* x, CvArr* y, int angleInDegrees=0)

Calculates Cartesian coordinates of 2d vectors represented in polar form.

Parameters:

• magnitude – The array of magnitudes. If it is NULL, the magnitudes are assumed to be all 1’s.
• angle – The array of angles, whether in radians or degrees
• x – The destination array of x-coordinates, may be set to NULL if it is not needed
• y – The destination array of y-coordinates, mau be set to NULL if it is not needed
• angleInDegrees – The flag indicating whether the angles are measured in radians, which is default mode, or in degrees

The function calculates either the x-coodinate, y-coordinate or both of every vector magnitude(I)*exp(angle(I)*j), j=sqrt(-1) :

x(I)=magnitude(I)*cos(angle(I)),
y(I)=magnitude(I)*sin(angle(I))

Pow

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void cvPow(const CvArr* src, CvArr* dst, double power)

Raises every array element to a power.

Parameters:

• src – The source array
• dst – The destination array, should be the same type as the source
• power – The exponent of power

The function raises every element of the input array to p :

That is, for a non-integer power exponent the absolute values of input array elements are used. However, it is possible to get true values for negative values using some extra operations, as the following example, computing the cube root of array elements, shows:

CvSize size = cvGetSize(src);
CvMat* mask = cvCreateMat(size.height, size.width, CV_8UC1);
cvCmpS(src, 0, mask, CV_CMP_LT); /* find negative elements */
cvPow(src, dst, 1./3);
cvSubRS(dst, cvScalarAll(0), dst, mask); /* negate the results of negative inputs */
cvReleaseMat(&mask);

For some values of power , such as integer values, 0.5, and -0.5, specialized faster algorithms are used.

Ptr?D

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uchar* cvPtr1D(const CvArr* arr, int idx0, int* type=NULL)

uchar* cvPtr2D(const CvArr* arr, int idx0, int idx1, int* type=NULL)

uchar* cvPtr3D(const CvArr* arr, int idx0, int idx1, int idx2, int* type=NULL)

uchar* cvPtrND(const CvArr* arr, int* idx, int* type=NULL, int createNode=1, unsigned* precalcHashval=NULL)

Return pointer to a particular array element.

Parameters:

• arr – Input array
• idx0 – The first zero-based component of the element index
• idx1 – The second zero-based component of the element index
• idx2 – The third zero-based component of the element index
• idx – Array of the element indices
• type – Optional output parameter: type of matrix elements
• createNode – Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already.
• precalcHashval – Optional input parameter for sparse matrices. If the pointer is not NULL, the function does not recalculate the node hash value, but takes it from the specified location. It is useful for speeding up pair-wise operations (TODO: provide an example)

The functions return a pointer to a specific array element. Number of array dimension should match to the number of indices passed to the function except for cvPtr1D function that can be used for sequential access to 1D, 2D or nD dense arrays.

The functions can be used for sparse arrays as well - if the requested node does not exist they create it and set it to zero.

All these as well as other functions accessing array elements ( Get , GetReal , Set , SetReal ) raise an error in case if the element index is out of range.

RNG

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CvRNG cvRNG(int64 seed=-1)

Initializes a random number generator state.

Parameters:

• seed – 64-bit value used to initiate a random sequence

The function initializes a random number generator and returns the state. The pointer to the state can be then passed to the RandInt , RandReal and RandArr functions. In the current implementation a multiply-with-carry generator is used.

RandArr

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void cvRandArr(CvRNG* rng, CvArr* arr, int distType, CvScalar param1, CvScalar param2)

Fills an array with random numbers and updates the RNG state.

Parameters:

• rng – RNG state initialized by RNG
• arr – The destination array
• distType –

  Distribution type

  • CV_RAND_UNI uniform distribution
  • CV_RAND_NORMAL normal or Gaussian distribution
• param1 – The first parameter of the distribution. In the case of a uniform distribution it is the inclusive lower boundary of the random numbers range. In the case of a normal distribution it is the mean value of the random numbers.
• param2 – The second parameter of the distribution. In the case of a uniform distribution it is the exclusive upper boundary of the random numbers range. In the case of a normal distribution it is the standard deviation of the random numbers.

The function fills the destination array with uniformly or normally distributed random numbers.

In the example below, the function is used to add a few normally distributed floating-point numbers to random locations within a 2d array.

/* let noisy_screen be the floating-point 2d array that is to be "crapped" */
CvRNG rng_state = cvRNG(0xffffffff);
int i, pointCount = 1000;
/* allocate the array of coordinates of points */
CvMat* locations = cvCreateMat(pointCount, 1, CV_32SC2);
/* arr of random point values */
CvMat* values = cvCreateMat(pointCount, 1, CV_32FC1);
CvSize size = cvGetSize(noisy_screen);

/* initialize the locations */
cvRandArr(&rng_state, locations, CV_RAND_UNI, cvScalar(0,0,0,0),
           cvScalar(size.width,size.height,0,0));

/* generate values */
cvRandArr(&rng_state, values, CV_RAND_NORMAL,
           cvRealScalar(100), // average intensity
           cvRealScalar(30) // deviation of the intensity
          );

/* set the points */
for(i = 0; i < pointCount; i++ )
{
    CvPoint pt = *(CvPoint*)cvPtr1D(locations, i, 0);
    float value = *(float*)cvPtr1D(values, i, 0);
    *((float*)cvPtr2D(noisy_screen, pt.y, pt.x, 0 )) += value;
}

/* not to forget to release the temporary arrays */
cvReleaseMat(&locations);
cvReleaseMat(&values);

/* RNG state does not need to be deallocated */

RandInt

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unsigned cvRandInt(CvRNG* rng)

Returns a 32-bit unsigned integer and updates RNG.

Parameters:

• rng – RNG state initialized by RandInit and, optionally, customized by RandSetRange (though, the latter function does not affect the discussed function outcome)

The function returns a uniformly-distributed random 32-bit unsigned integer and updates the RNG state. It is similar to the rand() function from the C runtime library, but it always generates a 32-bit number whereas rand() returns a number in between 0 and RAND_MAX which is or , depending on the platform.

The function is useful for generating scalar random numbers, such as points, patch sizes, table indices, etc., where integer numbers of a certain range can be generated using a modulo operation and floating-point numbers can be generated by scaling from 0 to 1 or any other specific range.

Here is the example from the previous function discussion rewritten using RandInt :

/* the input and the task is the same as in the previous sample. */
CvRNG rnggstate = cvRNG(0xffffffff);
int i, pointCount = 1000;
/* ... - no arrays are allocated here */
CvSize size = cvGetSize(noisygscreen);
/* make a buffer for normally distributed numbers to reduce call overhead */
#define bufferSize 16
float normalValueBuffer[bufferSize];
CvMat normalValueMat = cvMat(bufferSize, 1, CVg32F, normalValueBuffer);
int valuesLeft = 0;

for(i = 0; i < pointCount; i++ )
{
    CvPoint pt;
    /* generate random point */
    pt.x = cvRandInt(&rnggstate )
    pt.y = cvRandInt(&rnggstate )

    if(valuesLeft <= 0 )
    {
        /* fulfill the buffer with normally distributed numbers
           if the buffer is empty */
        cvRandArr(&rnggstate, &normalValueMat, CV_RAND_NORMAL,
                   cvRealScalar(100), cvRealScalar(30));
        valuesLeft = bufferSize;
    }
    *((float*)cvPtr2D(noisygscreen, pt.y, pt.x, 0 ) =
                                normalValueBuffer[--valuesLeft];
}

/* there is no need to deallocate normalValueMat because we have
both the matrix header and the data on stack. It is a common and efficient
practice of working with small, fixed-size matrices */

RandReal

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double cvRandReal(CvRNG* rng)

Returns a floating-point random number and updates RNG.

Parameters:

• rng – RNG state initialized by RNG

The function returns a uniformly-distributed random floating-point number between 0 and 1 (1 is not included).

Reduce

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void cvReduce(const CvArr* src, CvArr* dst, int dim = -1, int op=CV_REDUCE_SUM)

Reduces a matrix to a vector.

Parameters:

• src – The input matrix.
• dst – The output single-row/single-column vector that accumulates somehow all the matrix rows/columns.
• dim – The dimension index along which the matrix is reduced. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column and -1 means that the dimension is chosen automatically by analysing the dst size.
• op –

  The reduction operation. It can take of the following values:

  • CV_REDUCE_SUM The output is the sum of all of the matrix’s rows/columns.
  • CV_REDUCE_AVG The output is the mean vector of all of the matrix’s rows/columns.
  • CV_REDUCE_MAX The output is the maximum (column/row-wise) of all of the matrix’s rows/columns.
  • CV_REDUCE_MIN The output is the minimum (column/row-wise) of all of the matrix’s rows/columns.

The function reduces matrix to a vector by treating the matrix rows/columns as a set of 1D vectors and performing the specified operation on the vectors until a single row/column is obtained. For example, the function can be used to compute horizontal and vertical projections of an raster image. In the case of CV_REDUCE_SUM and CV_REDUCE_AVG the output may have a larger element bit-depth to preserve accuracy. And multi-channel arrays are also supported in these two reduction modes.

ReleaseData

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void cvReleaseData(CvArr* arr)

Releases array data.

Parameters:

• arr – Array header

The function releases the array data. In the case of CvMat or CvMatND it simply calls cvDecRefData(), that is the function can not deallocate external data. See also the note to CreateData .

ReleaseImage

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void cvReleaseImage(IplImage** image)

Deallocates the image header and the image data.

Parameters:

• image – Double pointer to the image header

This call is a shortened form of

if(*image )
{
    cvReleaseData(*image);
    cvReleaseImageHeader(image);
}

ReleaseImageHeader

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void cvReleaseImageHeader(IplImage** image)

Deallocates an image header.

Parameters:

• image – Double pointer to the image header

This call is an analogue of

if(image )
{
    iplDeallocate(*image, IPL_IMAGE_HEADER | IPL_IMAGE_ROI);
    *image = 0;
}

but it does not use IPL functions by default (see the CV_TURN_ON_IPL_COMPATIBILITY macro).

ReleaseMat

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void cvReleaseMat(CvMat** mat)

Deallocates a matrix.

Parameters:

• mat – Double pointer to the matrix

The function decrements the matrix data reference counter and deallocates matrix header. If the data reference counter is 0, it also deallocates the data.

if(*mat )
    cvDecRefData(*mat);
cvFree((void**)mat);

ReleaseMatND

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void cvReleaseMatND(CvMatND** mat)

Deallocates a multi-dimensional array.

Parameters:

• mat – Double pointer to the array

The function decrements the array data reference counter and releases the array header. If the reference counter reaches 0, it also deallocates the data.

if(*mat )
    cvDecRefData(*mat);
cvFree((void**)mat);

ReleaseSparseMat

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void cvReleaseSparseMat(CvSparseMat** mat)

Deallocates sparse array.

Parameters:

• mat – Double pointer to the array

The function releases the sparse array and clears the array pointer upon exit.

Repeat

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void cvRepeat(const CvArr* src, CvArr* dst)

Fill the destination array with repeated copies of the source array.

Parameters:

• src – Source array, image or matrix
• dst – Destination array, image or matrix

The function fills the destination array with repeated copies of the source array:

dst(i,j)=src(i mod rows(src), j mod cols(src))

So the destination array may be as larger as well as smaller than the source array.

ResetImageROI

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void cvResetImageROI(IplImage* image)

Resets the image ROI to include the entire image and releases the ROI structure.

Parameters:

• image – A pointer to the image header

This produces a similar result to the following , but in addition it releases the ROI structure.

cvSetImageROI(image, cvRect(0, 0, image->width, image->height ));
cvSetImageCOI(image, 0);

Reshape

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CvMat* cvReshape(const CvArr* arr, CvMat* header, int newCn, int newRows=0)

Changes shape of matrix/image without copying data.

Parameters:

• arr – Input array
• header – Output header to be filled
• newCn – New number of channels. ‘newCn = 0’ means that the number of channels remains unchanged.
• newRows – New number of rows. ‘newRows = 0’ means that the number of rows remains unchanged unless it needs to be changed according to newCn value.

The function initializes the CvMat header so that it points to the same data as the original array but has a different shape - different number of channels, different number of rows, or both.

The following example code creates one image buffer and two image headers, the first is for a 320x240x3 image and the second is for a 960x240x1 image:

IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3);
CvMat gray_mat_hdr;
IplImage gray_img_hdr, *gray_img;
cvReshape(color_img, &gray_mat_hdr, 1);
gray_img = cvGetImage(&gray_mat_hdr, &gray_img_hdr);

And the next example converts a 3x3 matrix to a single 1x9 vector:

CvMat* mat = cvCreateMat(3, 3, CV_32F);
CvMat row_header, *row;
row = cvReshape(mat, &row_header, 0, 1);

ReshapeMatND

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CvArr* cvReshapeMatND(const CvArr* arr, int sizeofHeader, CvArr* header, int newCn, int newDims, int* newSizes)

Changes the shape of a multi-dimensional array without copying the data.

#define cvReshapeND(arr, header, newCn, newDims, newSizes )   \
      cvReshapeMatND((arr), sizeof(*(header)), (header),         \
                      (newCn), (newDims), (newSizes))

param arr:Input array param sizeofHeader:  Size of output header to distinguish between IplImage, CvMat and CvMatND output headers param header:Output header to be filled param newCn:New number of channels. means that the number of channels remains unchanged. param newDims:New number of dimensions. means that the number of dimensions remains the same. param newSizes:Array of new dimension sizes. Only values are used, because the total number of elements must remain the same. Thus, if , newSizes array is not used.

The function is an advanced version of Reshape that can work with multi-dimensional arrays as well (though it can work with ordinary images and matrices) and change the number of dimensions.

Below are the two samples from the Reshape description rewritten using ReshapeMatND :

IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3);
IplImage gray_img_hdr, *gray_img;
gray_img = (IplImage*)cvReshapeND(color_img, &gray_img_hdr, 1, 0, 0);

...

/* second example is modified to convert 2x2x2 array to 8x1 vector */
int size[] = { 2, 2, 2 };
CvMatND* mat = cvCreateMatND(3, size, CV_32F);
CvMat row_header, *row;
row = (CvMat*)cvReshapeND(mat, &row_header, 0, 1, 0);

cvRound, cvFloor, cvCeil

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int cvRound(double value) int cvFloor(double value) int cvCeil(double value)

Converts a floating-point number to an integer.

Parameters:

• value – The input floating-point value

The functions convert the input floating-point number to an integer using one of the rounding modes. Round returns the nearest integer value to the argument. Floor returns the maximum integer value that is not larger than the argument. Ceil returns the minimum integer value that is not smaller than the argument. On some architectures the functions work much faster than the standard cast operations in C. If the absolute value of the argument is greater than , the result is not determined. Special values ( , NaN) are not handled.

ScaleAdd

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void cvScaleAdd(const CvArr* src1, CvScalar scale, const CvArr* src2, CvArr* dst)

Calculates the sum of a scaled array and another array.

Parameters:

• src1 – The first source array
• scale – Scale factor for the first array
• src2 – The second source array
• dst – The destination array

The function calculates the sum of a scaled array and another array:

All array parameters should have the same type and the same size.

Set

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void cvSet(CvArr* arr, CvScalar value, const CvArr* mask=NULL)

Sets every element of an array to a given value.

Parameters:

• arr – The destination array
• value – Fill value
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function copies the scalar value to every selected element of the destination array:

If array arr is of IplImage type, then is ROI used, but COI must not be set.

Set?D

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void cvSet1D(CvArr* arr, int idx0, CvScalar value)

void cvSet2D(CvArr* arr, int idx0, int idx1, CvScalar value)

void cvSet3D(CvArr* arr, int idx0, int idx1, int idx2, CvScalar value)

void cvSetND(CvArr* arr, int* idx, CvScalar value)

Change the particular array element.

Parameters:

• arr – Input array
• idx0 – The first zero-based component of the element index
• idx1 – The second zero-based component of the element index
• idx2 – The third zero-based component of the element index
• idx – Array of the element indices
• value – The assigned value

The functions assign the new value to a particular array element. In the case of a sparse array the functions create the node if it does not exist yet.

SetData

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void cvSetData(CvArr* arr, void* data, int step)

Assigns user data to the array header.

Parameters:

• arr – Array header
• data – User data
• step – Full row length in bytes

The function assigns user data to the array header. Header should be initialized before using cvCreate*Header , cvInit*Header or Mat (in the case of matrix) function.

SetIdentity

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void cvSetIdentity(CvArr* mat, CvScalar value=cvRealScalar(1))

Initializes a scaled identity matrix.

Parameters:

• mat – The matrix to initialize (not necesserily square)
• value – The value to assign to the diagonal elements

The function initializes a scaled identity matrix:

SetImageCOI

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void cvSetImageCOI(IplImage* image, int coi)

Sets the channel of interest in an IplImage.

Parameters:

• image – A pointer to the image header
• coi – The channel of interest. 0 - all channels are selected, 1 - first channel is selected, etc. Note that the channel indices become 1-based.

If the ROI is set to NULL and the coi is not 0, the ROI is allocated. Most OpenCV functions do not support the COI setting, so to process an individual image/matrix channel one may copy (via Copy or Split ) the channel to a separate image/matrix, process it and then copy the result back (via Copy or Merge ) if needed.

SetImageROI

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void cvSetImageROI(IplImage* image, CvRect rect)

Sets an image Region Of Interest (ROI) for a given rectangle.

Parameters:

• image – A pointer to the image header
• rect – The ROI rectangle

If the original image ROI was NULL and the rect is not the whole image, the ROI structure is allocated.

Most OpenCV functions support the use of ROI and treat the image rectangle as a separate image. For example, all of the pixel coordinates are counted from the top-left (or bottom-left) corner of the ROI, not the original image.

SetReal?D

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void cvSetReal1D(CvArr* arr, int idx0, double value)

void cvSetReal2D(CvArr* arr, int idx0, int idx1, double value)

void cvSetReal3D(CvArr* arr, int idx0, int idx1, int idx2, double value)

void cvSetRealND(CvArr* arr, int* idx, double value)

Change a specific array element.

Parameters:

• arr – Input array
• idx0 – The first zero-based component of the element index
• idx1 – The second zero-based component of the element index
• idx2 – The third zero-based component of the element index
• idx – Array of the element indices
• value – The assigned value

The functions assign a new value to a specific element of a single-channel array. If the array has multiple channels, a runtime error is raised. Note that the Set*D function can be used safely for both single-channel and multiple-channel arrays, though they are a bit slower.

In the case of a sparse array the functions create the node if it does not yet exist.

SetZero

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void cvSetZero(CvArr* arr)

Clears the array.

#define cvZero cvSetZero

param arr:Array to be cleared

The function clears the array. In the case of dense arrays (CvMat, CvMatND or IplImage), cvZero(array) is equivalent to cvSet(array,cvScalarAll(0),0). In the case of sparse arrays all the elements are removed.

Solve

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int cvSolve(const CvArr* src1, const CvArr* src2, CvArr* dst, int method=CV_LU)

Solves a linear system or least-squares problem.

Parameters:

• A – The source matrix
• B – The right-hand part of the linear system
• X – The output solution
• method –

  The solution (matrix inversion) method

  • CV_LU Gaussian elimination with optimal pivot element chosen
  • CV_SVD Singular value decomposition (SVD) method
  • CV_SVD_SYM SVD method for a symmetric positively-defined matrix.

The function solves a linear system or least-squares problem (the latter is possible with SVD methods):

If CV_LU method is used, the function returns 1 if src1 is non-singular and 0 otherwise; in the latter case dst is not valid.

SolveCubic

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void cvSolveCubic(const CvArr* coeffs, CvArr* roots)

Finds the real roots of a cubic equation.

Parameters:

• coeffs – The equation coefficients, an array of 3 or 4 elements
• roots – The output array of real roots which should have 3 elements

The function finds the real roots of a cubic equation:

If coeffs is a 4-element vector:

or if coeffs is 3-element vector:

The function returns the number of real roots found. The roots are stored to root array, which is padded with zeros if there is only one root.

Split

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void cvSplit(const CvArr* src, CvArr* dst0, CvArr* dst1, CvArr* dst2, CvArr* dst3)

Divides multi-channel array into several single-channel arrays or extracts a single channel from the array.

Parameters:

• src – Source array
• dst0 – Destination channel 0
• dst1 – Destination channel 1
• dst2 – Destination channel 2
• dst3 – Destination channel 3

The function divides a multi-channel array into separate single-channel arrays. Two modes are available for the operation. If the source array has N channels then if the first N destination channels are not NULL, they all are extracted from the source array; if only a single destination channel of the first N is not NULL, this particular channel is extracted; otherwise an error is raised. The rest of the destination channels (beyond the first N) must always be NULL. For IplImage Copy with COI set can be also used to extract a single channel from the image.

Sqrt

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float cvSqrt(float value)

Calculates the square root.

Parameters:

• value – The input floating-point value

The function calculates the square root of the argument. If the argument is negative, the result is not determined.

Sub

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void cvSub(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL)

Computes the per-element difference between two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function subtracts one array from another one:

dst(I)=src1(I)-src2(I) if mask(I)!=0

All the arrays must have the same type, except the mask, and the same size (or ROI size). For types that have limited range this operation is saturating.

SubRS

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void cvSubRS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)

Computes the difference between a scalar and an array.

Parameters:

• src – The first source array
• value – Scalar to subtract from
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function subtracts every element of source array from a scalar:

dst(I)=value-src(I) if mask(I)!=0

All the arrays must have the same type, except the mask, and the same size (or ROI size). For types that have limited range this operation is saturating.

SubS

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void cvSubS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)

Computes the difference between an array and a scalar.

Parameters:

• src – The source array
• value – Subtracted scalar
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function subtracts a scalar from every element of the source array:

dst(I)=src(I)-value if mask(I)!=0

All the arrays must have the same type, except the mask, and the same size (or ROI size). For types that have limited range this operation is saturating.

Sum

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CvScalar cvSum(const CvArr* arr)

Adds up array elements.

Parameters:

• arr – The array

The function calculates the sum S of array elements, independently for each channel:

If the array is IplImage and COI is set, the function processes the selected channel only and stores the sum to the first scalar component.

SVBkSb

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void cvSVBkSb(const CvArr* W, const CvArr* U, const CvArr* V, const CvArr* B, CvArr* X, int flags)

Performs singular value back substitution.

Parameters:

• W – Matrix or vector of singular values
• U – Left orthogonal matrix (tranposed, perhaps)
• V – Right orthogonal matrix (tranposed, perhaps)
• B – The matrix to multiply the pseudo-inverse of the original matrix A by. This is an optional parameter. If it is omitted then it is assumed to be an identity matrix of an appropriate size (so that X will be the reconstructed pseudo-inverse of A ).
• X – The destination matrix: result of back substitution
• flags – Operation flags, should match exactly to the flags passed to SVD

The function calculates back substitution for decomposed matrix A (see SVD description) and matrix B :

where

and is a small number that depends on the matrix data type.

This function together with SVD is used inside Invert and Solve , and the possible reason to use these (svd and bksb) “low-level” function, is to avoid allocation of temporary matrices inside the high-level counterparts (inv and solve).

SVD

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void cvSVD(CvArr* A, CvArr* W, CvArr* U=NULL, CvArr* V=NULL, int flags=0)

Performs singular value decomposition of a real floating-point matrix.

Parameters:

• A – Source matrix
• W – Resulting singular value diagonal matrix ( or ) or vector of the singular values
• U – Optional left orthogonal matrix, (when CV_SVD_U_T is not set), or (when CV_SVD_U_T is set), or (regardless of CV_SVD_U_T flag).
• V – Optional right orthogonal matrix, (when CV_SVD_V_T is not set), or (when CV_SVD_V_T is set), or (regardless of CV_SVD_V_T flag).
• flags –

  Operation flags; can be 0 or a combination of the following values:

  • CV_SVD_MODIFY_A enables modification of matrix A during the operation. It speeds up the processing.
  • CV_SVD_U_T means that the transposed matrix U is returned. Specifying the flag speeds up the processing.
  • CV_SVD_V_T means that the transposed matrix V is returned. Specifying the flag speeds up the processing.

The function decomposes matrix A into the product of a diagonal matrix and two

orthogonal matrices:

where is a diagonal matrix of singular values that can be coded as a 1D vector of singular values and and . All the singular values are non-negative and sorted (together with and columns) in descending order.

An SVD algorithm is numerically robust and its typical applications include:

• accurate eigenvalue problem solution when matrix A is a square, symmetric, and positively defined matrix, for example, when

  it is a covariance matrix.

  in this case will be a vector/matrix

  of the eigenvalues, and

  will be a matrix of the eigenvectors.

• accurate solution of a poor-conditioned linear system.

• least-squares solution of an overdetermined linear system. This and the preceeding is done by using the Solve function with the CV_SVD method.

• accurate calculation of different matrix characteristics such as the matrix rank (the number of non-zero singular values), condition number (ratio of the largest singular value to the smallest one), and determinant (absolute value of the determinant is equal to the product of singular values).

Trace

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CvScalar cvTrace(const CvArr* mat)

Returns the trace of a matrix.

Parameters:

• mat – The source matrix

The function returns the sum of the diagonal elements of the matrix src1 .

Transform

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void cvTransform(const CvArr* src, CvArr* dst, const CvMat* transmat, const CvMat* shiftvec=NULL)

Performs matrix transformation of every array element.

Parameters:

• src – The first source array
• dst – The destination array
• transmat – Transformation matrix
• shiftvec – Optional shift vector

The function performs matrix transformation of every element of array src and stores the results in dst :

That is, every element of an N -channel array src is considered as an N -element vector which is transformed using a matrix transmat and shift vector shiftvec into an element of M -channel array dst . There is an option to embedd shiftvec into transmat . In this case transmat should be a matrix and the rightmost column is treated as the shift vector.

Both source and destination arrays should have the same depth and the same size or selected ROI size. transmat and shiftvec should be real floating-point matrices.

The function may be used for geometrical transformation of n dimensional point set, arbitrary linear color space transformation, shuffling the channels and so forth.

Transpose

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void cvTranspose(const CvArr* src, CvArr* dst)

Transposes a matrix.

Parameters:

• src – The source matrix
• dst – The destination matrix

The function transposes matrix src1 :

Note that no complex conjugation is done in the case of a complex matrix. Conjugation should be done separately: look at the sample code in XorS for an example.

Xor

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void cvXor(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL)

Performs per-element bit-wise “exclusive or” operation on two arrays.

Parameters:

• src1 – The first source array
• src2 – The second source array
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function calculates per-element bit-wise logical conjunction of two arrays:

dst(I)=src1(I)^src2(I) if mask(I)!=0

In the case of floating-point arrays their bit representations are used for the operation. All the arrays must have the same type, except the mask, and the same size.

XorS

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void cvXorS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL)

Performs per-element bit-wise “exclusive or” operation on an array and a scalar.

Parameters:

• src – The source array
• value – Scalar to use in the operation
• dst – The destination array
• mask – Operation mask, 8-bit single channel array; specifies elements of the destination array to be changed

The function XorS calculates per-element bit-wise conjunction of an array and a scalar:

dst(I)=src(I)^value if mask(I)!=0

Prior to the actual operation, the scalar is converted to the same type as that of the array(s). In the case of floating-point arrays their bit representations are used for the operation. All the arrays must have the same type, except the mask, and the same size

The following sample demonstrates how to conjugate complex vector by switching the most-significant bit of imaging part:

float a[] = { 1, 0, 0, 1, -1, 0, 0, -1 }; /* 1, j, -1, -j */
CvMat A = cvMat(4, 1, CV_32FC2, &a);
int i, negMask = 0x80000000;
cvXorS(&A, cvScalar(0, *(float*)&negMask, 0, 0 ), &A, 0);
for(i = 0; i < 4; i++ )
    printf("(%.1f, %.1f) ", a[i*2], a[i*2+1]);

The code should print:

(1.0,0.0) (0.0,-1.0) (-1.0,0.0) (0.0,1.0)

mGet

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double cvmGet(const CvMat* mat, int row, int col)

Returns the particular element of single-channel floating-point matrix.

Parameters:

• mat – Input matrix
• row – The zero-based index of row
• col – The zero-based index of column

The function is a fast replacement for GetReal2D in the case of single-channel floating-point matrices. It is faster because it is inline, it does fewer checks for array type and array element type, and it checks for the row and column ranges only in debug mode.

mSet

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void cvmSet(CvMat* mat, int row, int col, double value)

Returns a specific element of a single-channel floating-point matrix.

Parameters:

• mat – The matrix
• row – The zero-based index of row
• col – The zero-based index of column
• value – The new value of the matrix element

The function is a fast replacement for SetReal2D in the case of single-channel floating-point matrices. It is faster because it is inline, it does fewer checks for array type and array element type, and it checks for the row and column ranges only in debug mode.