Face recognition using Co-occurrence Histograms of Oriented Gradients

Recently, Histogram of Oriented Gradient (HOG) is applied in face recognition. In this paper, we apply Co-occurrence of Oriented Gradient (CoHOG), which is an extension of HOG, on the face recognition problem. Some weighted functions for magnitude gradient are tested. We also proposed a weighted approach for CoHOG, where a weight value is set for each subregion of face image. Numerical experiments performed on Yale and ORL datasets show that 1) CoHOG has recognition accuracy higher than HOG; 2) using gradient magnitude in CoHOG improves recognition results; and 3) weighted CoHOG approach improves accuracy recognition rate. The recognition results using CoHOG are competitive with some of the state of the art methods. This proves the effectiveness of CoHOG descriptor for face recognition.