Extracting HoG Features using OpenCV

You can use hog class in opencv as follows

HOGDescriptor hog;
vector<float> ders;
vector<Point> locs;

This function computes the hog features for you

hog.compute(grayImg, ders, Size(32, 32), Size(0, 0), locs);

The HOG features computed for grayImg are stored in ders vector to make it into a matrix, which can be used later for training.

Mat Hogfeat(ders.size(), 1, CV_32FC1);

for(int i=0;i<ders.size();i++)
    Hogfeat.at<float>(i,0)=ders.at(i);

Now your HOG features are stored in Hogfeat matrix.

You can also set the window size, cell size and block size by using object hog as follows:

hog.blockSize = 16;
hog.cellSize = 4;
hog.blockStride = 8;

// This is for comparing the HOG features of two images without using any SVM 
// (It is not an efficient way but useful when you want to compare only few or two images)
// Simple distance
// Consider you have two HOG feature vectors for two images Hogfeat1 and Hogfeat2 and those are same size.

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

if (distance < Threshold)
    cout<<"Two images are of same class"<<endl;
else
    cout<<"Two images are of different class"<<endl;

Hope it is useful 🙂