December 2014
Beginner to intermediate
575 pages
19h 37m
English
Content preview from Learning OpenCV, 2nd Edition
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be a single-channel byte or floating-point image of size (image.width – templ.width + 1,
image.height – templ.height + 1). The matching method is chosen from one of the options
listed below (we use I to denote the input image, T the template, and R the result image in the definitions).
For each of these, there is also a normalized version
10
:
Figure 7-8: cv::matchTemplate() sweeps a template image patch across another image looking for
matches
Square difference matching method (method = cv::TM_SQDIFF)
These methods match the squared difference, so a perfect match will be 0 and bad matches will be large:
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Normalized square difference matching method (method = cv::TM_SQDIFF_NORMED)
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Correlation matching methods (method = cv::TM_CCORR)
These methods multiplicatively match the template against the image, so a perfect match will be large and
bad matches will be small or zero.
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Normalized cross-correlation matching method (method = cv::TM_SQDIFF_NORMED)
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The normalized versions were first developed by Galton [Galton] as described by Rodgers [Rodgers88]. The
normalized methods are useful, as they can help reduce ...
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