openCV matchTemplate函数不同参数对应的相似性度量

Compares a template against overlapped image regions.

C++:  void  matchTemplate (InputArray  image, InputArray  templ, OutputArray  result, int  method )

Python:   cv2. matchTemplate (image, templ, method [, result ] ) → result

C:  void  cvMatchTemplate (const CvArr*  image, const CvArr*  templ, CvArr*  result, int  method )

Python:   cv. MatchTemplate (image, templ, result, method ) → None

Parameters:	image – Image where the search is running. It must be 8-bit or 32-bit floating-point. templ – Searched template. It must be not greater than the source image and have the same data type. result – Map of comparison results. It must be single-channel 32-bit floating-point. If imageis  and templ is  , then result is  . method – Parameter specifying the comparison method (see below).

The function slides through image , compares the overlapped patches of size  against templ using the specified method and stores the comparison results in result . Here are the formulae for the available comparison methods ( denotes image,  template,  result ). The summation is done over template and/or the image patch:  * method=CV_TM_SQDIFF

• method=CV_TM_SQDIFF_NORMED

• method=CV_TM_CCORR

• method=CV_TM_CCORR_NORMED

• method=CV_TM_CCOEFF

  where

• method=CV_TM_CCOEFF_NORMED

After the function finishes the comparison, the best matches can be found as global minimums (when CV_TM_SQDIFF was used) or maximums (when CV_TM_CCORR or CV_TM_CCOEFF was used) using the minMaxLoc() function. In case of a color image, template summation in the numerator and each sum in the denominator is done over all of the channels and separate mean values are used for each channel. That is, the function can take a color template and a color image. The result will still be a single-channel image, which is easier to analyze.