Adds an image to the accumulator.
void accumulate
(InputArray src, InputOutputArray dst, InputArray mask=noArray() )¶
cv2.
accumulate
(src, dst[, mask]) → None¶
void cvAcc
(const CvArr* image, CvArr* sum, const CvArr* mask=NULL )¶
cv.
Acc
(image, sum, mask=None) → None¶Parameters: 


The function adds src
or some of its elements to dst
:
The function supports multichannel images. Each channel is processed independently.
The functions accumulate*
can be used, for example, to collect statistics of a scene background viewed by a still camera and for the further foregroundbackground segmentation.
Adds the square of a source image to the accumulator.
void accumulateSquare
(InputArray src, InputOutputArray dst, InputArray mask=noArray() )¶
cv2.
accumulateSquare
(src, dst[, mask]) → None¶
void cvSquareAcc
(const CvArr* image, CvArr* sqsum, const CvArr* mask=NULL )¶
cv.
SquareAcc
(image, sqsum, mask=None) → None¶Parameters: 


The function adds the input image src
or its selected region, raised to a power of 2, to the accumulator dst
:
The function supports multichannel images. Each channel is processed independently.
Adds the perelement product of two input images to the accumulator.
void accumulateProduct
(InputArray src1, InputArray src2, InputOutputArray dst, InputArray mask=noArray() )¶
cv2.
accumulateProduct
(src1, src2, dst[, mask]) → None¶
void cvMultiplyAcc
(const CvArr* image1, const CvArr* image2, CvArr* acc, const CvArr* mask=NULL )¶
cv.
MultiplyAcc
(image1, image2, acc, mask=None) → None¶Parameters: 


The function adds the product of two images or their selected regions to the accumulator dst
:
The function supports multichannel images. Each channel is processed independently.
See also
Updates a running average.
void accumulateWeighted
(InputArray src, InputOutputArray dst, double alpha, InputArray mask=noArray() )¶
cv2.
accumulateWeighted
(src, dst, alpha[, mask]) → None¶
void cvRunningAvg
(const CvArr* image, CvArr* acc, double alpha, const CvArr* mask=NULL )¶
cv.
RunningAvg
(image, acc, alpha, mask=None) → None¶Parameters: 


The function calculates the weighted sum of the input image src
and the accumulator dst
so that dst
becomes a running average of a frame sequence:
That is, alpha
regulates the update speed (how fast the accumulator “forgets” about earlier images).
The function supports multichannel images. Each channel is processed independently.
See also
The function is used to detect translational shifts that occur between two images. The operation takes advantage of the Fourier shift theorem for detecting the translational shift in the frequency domain. It can be used for fast image registration as well as motion estimation. For more information please see http://en.wikipedia.org/wiki/Phase_correlation .
Calculates the crosspower spectrum of two supplied source arrays. The arrays are padded if needed with getOptimalDFTSize()
.
Point2d phaseCorrelate
(InputArray src1, InputArray src2, InputArray window=noArray())¶
Point2d phaseCorrelateRes
(InputArray src1, InputArray src2, InputArray window, double* response=0)¶Parameters: 


Return value: detected phase shift (subpixel) between the two arrays.
The function performs the following equations
First it applies a Hanning window (see http://en.wikipedia.org/wiki/Hann_function) to each image to remove possible edge effects. This window is cached until the array size changes to speed up processing time.
Next it computes the forward DFTs of each source array:
where is the forward DFT.
It then computes the crosspower spectrum of each frequency domain array:
Next the crosscorrelation is converted back into the time domain via the inverse DFT:
Finally, it computes the peak location and computes a 5x5 weighted centroid around the peak to achieve subpixel accuracy.
If nonzero, the response parameter is computed as the sum of the elements of r within the 5x5 centroid around the peak location. It is normalized to a maximum of 1 (meaning there is a single peak) and will be smaller when there are multiple peaks.
This function computes a Hanning window coefficients in two dimensions. See http://en.wikipedia.org/wiki/Hann_function and http://en.wikipedia.org/wiki/Window_function for more information.
void createHanningWindow
(OutputArray dst, Size winSize, int type)¶Parameters: 


An example is shown below:
// create hanning window of size 100x100 and type CV_32F
Mat hann;
createHanningWindow(hann, Size(100, 100), CV_32F);
See also