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I have currently implemented a way to calculate HOG descriptors using cv::HOGDescriptor() . I have done this for two images and calculated a similarity index between the two images using a basic distance measure.

A good match is something I define as a similarity value below 50. A perfect match has a similarity value of 0

However, when comparing these two almost identical images, I get confusing results (i.e. a high value). Below attached is my code and the 2 images.

Can anyone please tell me what is going wrong? i.e. Why is there a high similarity value when the images are very similar.

    #include <iostream>
    #include <opencv2/core/core.hpp>
    #include <opencv2/imgproc/imgproc.hpp>
    #include <math.h>
    #include "opencv2/ocl/ocl.hpp"
    #include "opencv2/highgui/highgui.hpp"

using namespace std;
using namespace cv;

int main()
{
   Mat image(imread("R2.jpg",1));
   resize(image, image, Size(64,128) );
   Mat img;
   cvtColor(image, img, CV_RGB2GRAY);

   Mat image2(imread("R2-roi.jpg",1));
   resize(image2, image2, Size(64,128) );
   Mat img2;
   cvtColor(image2, img2, CV_RGB2GRAY);

   vector<float> features;
   vector<Point> locations;
   vector<float> features2;
   vector<Point> locations2;

   HOGDescriptor *hog = new HOGDescriptor();
   HOGDescriptor *hog2 = new HOGDescriptor();

   hog->compute(img,features,Size(32,32), Size(0,0),locations);
   cout<<features.size()<<endl;;

   hog2->compute(img2,features2,Size(32,32), Size(0,0),locations2);
   cout<<features2.size()<<endl;

   Mat Hogfeat;
   Hogfeat.create(features.size(),1,CV_32FC1);
   for(int i=0; i<features.size(); i++)
      Hogfeat.at<float>(i,0)=features.at(i);

   Mat Hogfeat2;
   Hogfeat2.create(features2.size(),1,CV_32FC1);
   for(int i=0; i<features2.size(); i++)
      Hogfeat2.at<float>(i,0)=features2.at(i);

   double distance=0;
   for(int i=0; i<Hogfeat.rows; i++)
   {
      distance+= abs(Hogfeat.at<float>(i,0) - Hogfeat2.at<float>(i,0));
   }
   cout << distance <<endl;

   return 0;
}

R2.jpg R2-roi.jpg