OPENCV implementation of histogram method for image similarity calculation

Operation Steps:

1. Load images (grayscale or color) and make them consistent in size;

2. If the color map, improve the line color space transformation, from RGB to HSV, if the gray-scale map does not need to transform;

3. If the histogram is calculated directly, and the histogram is normalized;

4. If the color graph, the color histogram is computed, and the color histogram normalization;

5. Use similarity formulas, such as correlation coefficients, chi-square, intersections, or babbitt distances, to calculate the similarity value.

String strsrcimagename = "Src.jpg"; Cv::mat matsrc, matSrc1, matsrc2;matsrc = Cv::imread (Strsrcimagename, Cv_load_image_ unchanged); Cv::resize (MATSRC, MatSrc1, Cv::size (357, 419), 0, 0, cv::inter_nearest); Cv::resize (MATSRC, MATSRC2, CV:: Size (2177, 3233), 0, 0, Cv::inter_lanczos4), Cv::mat matDst1, matdst2;cv::size sizeimage = cv::size (500, 500); Cv::resize (MatSrc1, MatDst1, sizeimage, 0, 0, cv::inter_cubic);//cv::flip (MatDst1, MatDst1, 1); Cv::resize (MATSRC2, MatDst2, sizeimage, 0, 0, cv::inter_cubic); if (matsrc.channels () = = 1) {int histsize = 256;float range[] = {0, 256};const float* Histrange = {Range};bool uniform = true;bool accumulate = False;cv::mat Hist1, hist2;cv::calchist (&matDst1, 1, 0, Cv::mat (), Hist1, 1, &histsize, &histrange, uniform, accumulate); Cv::normalize (Hist1, Hist1, 0, 1, cv::norm_mi NMAX,-1, Cv::mat ()); Cv::calchist (&matdst2, 1, 0, Cv::mat (), Hist2, 1, &histsize, &histrange, uniform, Accumu Late); Cv::normalize (Hist2, Hist2, 0, 1, Cv::norm_minmaX,-1, Cv::mat ());d ouble dsimilarity = cv::comparehist (Hist1, Hist2, Cv_comp_correl);//,cv_comp_chisqr,cv_comp_ intersect,cv_comp_bhattacharyyacout<< "similarity =" &LT;&LT;DSIMILARITY&LT;&LT;ENDL;} else {Cv::cvtcolor (MatDst1, MatDst1, CV::COLOR_BGR2HSV); Cv::cvtcolor (MatDst2, MatDst2, CV::COLOR_BGR2HSV); int H_bins = S_bins = 60;int histsize[] = {h_bins, s_bins};float h_ranges[] = {0, 180};float s_ranges[] = {0, 256};const float* r Anges[] = {h_ranges, s_ranges};int channels[] = {0, 1};cv::matnd hist1, Hist2;cv::calchist (&matdst1, 1, channels, CV:: Mat (), Hist1, 2, histsize, ranges, true, false) Cv::normalize (Hist1, Hist1, 0, 1, Cv::norm_minmax,-1, Cv::mat ()); Cv::calc Hist (&matdst2, 1, channels, Cv::mat (), Hist2, 2, histsize, ranges, true, false), Cv::normalize (Hist2, Hist2, 0, 1, CV:: Norm_minmax,-1, Cv::mat ());d ouble dsimilarity = cv::comparehist (Hist1, Hist2, Cv_comp_correl);cout<< " similarity = "&LT;&LT;DSIMILARITY&LT;&LT;ENDL;}

OPENCV implementation of histogram method for image similarity calculation