Weber Local Gradient Pattern (WLGP) Method for Face Recognition

Robust and discriminative feature extraction without any controlled light intensity condition is vital for a real-time face recognition system. The Weber Local Descriptor (WLD) is an effective and robust face representation algorithm. However, WLD actually exploits the contrast information, which can still be sensitive to illumination changes. To overcome this problem, in this article, we take gradients into account and propose a novel operator, called Weber Local Gradient Descriptor (WLGD).This method produces the fusion characteristic and describes the facial texture through the computation of horizontal and diagonal gradients respectively. Experimental results on the ORL face database and infrared face database demonstrate that the proposed WLGD algorithm outperforms some state-of-art methods.