Face recognition based on modular histogram of oriented directional features

This paper presents an illumination invariant face recognition system that uses local directional pattern descriptor and modular histogram. The proposed Modular Histogram of Oriented Directional Features (MHODF) is an oriented local descriptor that is able to encode various patterns of face images under different lighting conditions. It employs the edge response values in different directions to encode each sub-image texture and produces multi-region histograms for each image. The edge responses are very important and play the main role for improving the face recognition accuracy. Therefore, we present the effectiveness of using different directional masks for detecting the edge responses on face recognition accuracy, such as Prewitt kernels, Kirsch masks, Sobel kernels, and Gaussian derivative masks. The performance evaluation of the proposed MHODF algorithm is conducted on several publicly available databases and observed promising recognition rates.