New normalization in histogram comparison tutorial to use Kullback-Leibler divergence #27516
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The Kullback-Leibler divergence works with histogram that have integral = 1, otherwise it can return negative values. The normalization of the histograms have been changed accordingly, and all the six comparison methods have been used in the histogram comparison tutorial.
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The Kullback-Leibler divergence works with histograms that have integral = 1, otherwise it can return negative values. Currently, in the histogram comparison tutorial the histograms have been normalized to have values between 0 and 1, not to have the sum of the values equal to 1.
The normalization of the histograms have been changed (
NORM_L1instead ofNORM_MINMAX). The Alternative Chi-Square and the Kullback-Leibler divergence have been added. The codes have been tested. The .markdown file has been updated (new C++ results).Moreover, the intersection now returns values between 1 and 0, like the correlation.
The sentence "We can observe that the matches between the test 1 and test 2 with respect to the base are worse, which again, was expected" has been removed from the .markdown file, because it is not longer true for the Chi-Square. In any case, the documentation already said that "the matching should not be very good" for both test images, and it didn't say that the comparison with test 1 was expected to be better than test 2.
Thanks to @LucaGMartino for the support.
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Patch to opencv_extra has the same branch name.