Mirrors/opencv
0
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-01-18 17:21:42 +01:00
Code Packages Releases Activity

New normalization in histogram comparison tutorial to use KV divergence

Browse Source 
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.
This commit is contained in:
ClaudioMartino
2025-07-05 11:15:35 +02:00
parent c48dad1d9d
commit 6a5884c04f
4 changed files with 37 additions and 29 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp
View File

@@ -66,20 +66,20 @@ int main( int argc, char** argv )
Mat hist_base, hist_half_down, hist_test1, hist_test2;
calcHist( &hsv_base, 1, channels, Mat(), hist_base, 2, histSize, ranges, true, false );
normalize( hist_base, hist_base, 0, 1, NORM_MINMAX, -1, Mat() );
normalize( hist_base, hist_base, 1, 0, NORM_L1, -1, Mat() );
calcHist( &hsv_half_down, 1, channels, Mat(), hist_half_down, 2, histSize, ranges, true, false );
normalize( hist_half_down, hist_half_down, 0, 1, NORM_MINMAX, -1, Mat() );
normalize( hist_half_down, hist_half_down, 1, 0, NORM_L1, -1, Mat() );
calcHist( &hsv_test1, 1, channels, Mat(), hist_test1, 2, histSize, ranges, true, false );
normalize( hist_test1, hist_test1, 0, 1, NORM_MINMAX, -1, Mat() );
normalize( hist_test1, hist_test1, 1, 0, NORM_L1, -1, Mat() );
calcHist( &hsv_test2, 1, channels, Mat(), hist_test2, 2, histSize, ranges, true, false );
normalize( hist_test2, hist_test2, 0, 1, NORM_MINMAX, -1, Mat() );
normalize( hist_test2, hist_test2, 1, 0, NORM_L1, -1, Mat() );
//! [Calculate the histograms for the HSV images]
//! [Apply the histogram comparison methods]
for( int compare_method = 0; compare_method < 4; compare_method++ )
for( int compare_method = 0; compare_method < 6; compare_method++ )
{
double base_base = compareHist( hist_base, hist_base, compare_method );
double base_half = compareHist( hist_base, hist_half_down, compare_method );

10
samples/java/tutorial_code/Histograms_Matching/histogram_comparison/CompareHistDemo.java
View File

@@ -52,23 +52,23 @@ class CompareHist {
List<Mat> hsvBaseList = Arrays.asList(hsvBase);
Imgproc.calcHist(hsvBaseList, new MatOfInt(channels), new Mat(), histBase, new MatOfInt(histSize), new MatOfFloat(ranges), false);
Core.normalize(histBase, histBase, 0, 1, Core.NORM_MINMAX);
Core.normalize(histBase, histBase, 1, 0, Core.NORM_L1);
List<Mat> hsvHalfDownList = Arrays.asList(hsvHalfDown);
Imgproc.calcHist(hsvHalfDownList, new MatOfInt(channels), new Mat(), histHalfDown, new MatOfInt(histSize), new MatOfFloat(ranges), false);
Core.normalize(histHalfDown, histHalfDown, 0, 1, Core.NORM_MINMAX);
Core.normalize(histHalfDown, histHalfDown, 1, 0, Core.NORM_L1);
List<Mat> hsvTest1List = Arrays.asList(hsvTest1);
Imgproc.calcHist(hsvTest1List, new MatOfInt(channels), new Mat(), histTest1, new MatOfInt(histSize), new MatOfFloat(ranges), false);
Core.normalize(histTest1, histTest1, 0, 1, Core.NORM_MINMAX);
Core.normalize(histTest1, histTest1, 1, 0, Core.NORM_L1);
List<Mat> hsvTest2List = Arrays.asList(hsvTest2);
Imgproc.calcHist(hsvTest2List, new MatOfInt(channels), new Mat(), histTest2, new MatOfInt(histSize), new MatOfFloat(ranges), false);
Core.normalize(histTest2, histTest2, 0, 1, Core.NORM_MINMAX);
Core.normalize(histTest2, histTest2, 1, 0, Core.NORM_L1);
//! [Calculate the histograms for the HSV images]
//! [Apply the histogram comparison methods]
for( int compareMethod = 0; compareMethod < 4; compareMethod++ ) {
for( int compareMethod = 0; compareMethod < 6; compareMethod++ ) {
double baseBase = Imgproc.compareHist( histBase, histBase, compareMethod );
double baseHalf = Imgproc.compareHist( histBase, histHalfDown, compareMethod );
double baseTest1 = Imgproc.compareHist( histBase, histTest1, compareMethod );

10
samples/python/tutorial_code/Histograms_Matching/histogram_comparison/compareHist_Demo.py
View File

@@ -45,20 +45,20 @@ channels = [0, 1]
## [Calculate the histograms for the HSV images]
hist_base = cv.calcHist([hsv_base], channels, None, histSize, ranges, accumulate=False)
cv.normalize(hist_base, hist_base, alpha=0, beta=1, norm_type=cv.NORM_MINMAX)
cv.normalize(hist_base, hist_base, alpha=1, beta=0, norm_type=cv.NORM_L1)
hist_half_down = cv.calcHist([hsv_half_down], channels, None, histSize, ranges, accumulate=False)
cv.normalize(hist_half_down, hist_half_down, alpha=0, beta=1, norm_type=cv.NORM_MINMAX)
cv.normalize(hist_half_down, hist_half_down, alpha=1, beta=0, norm_type=cv.NORM_L1)
hist_test1 = cv.calcHist([hsv_test1], channels, None, histSize, ranges, accumulate=False)
cv.normalize(hist_test1, hist_test1, alpha=0, beta=1, norm_type=cv.NORM_MINMAX)
cv.normalize(hist_test1, hist_test1, alpha=1, beta=0, norm_type=cv.NORM_L1)
hist_test2 = cv.calcHist([hsv_test2], channels, None, histSize, ranges, accumulate=False)
cv.normalize(hist_test2, hist_test2, alpha=0, beta=1, norm_type=cv.NORM_MINMAX)
cv.normalize(hist_test2, hist_test2, alpha=1, beta=0, norm_type=cv.NORM_L1)
## [Calculate the histograms for the HSV images]
## [Apply the histogram comparison methods]
for compare_method in range(4):
for compare_method in range(6):
base_base = cv.compareHist(hist_base, hist_base, compare_method)
base_half = cv.compareHist(hist_base, hist_half_down, compare_method)
base_test1 = cv.compareHist(hist_base, hist_test1, compare_method)