Recognition of Partially Occluded Face Using Gradientface and Local Binary Patterns

Currently one of the most important challenges of face recognition systems is the problem of occlusion, which is quite common in real applications. There are several studies in the literature treating this problem, but no defined or robust solution is agreed. The focus of this work is to develop face recognition method with sunglasses and scarf occlusion. We propose a robust approach which consists in detecting the face region that does not have occlusion and uses this region to obtain the recognition. To classify the occluded and non-occluded parts, a Multi-Layer Perceptron (MLP) is applied. While for the recognition a combined Gradientface and Local Binary Pattern (LBP) are used. Gradientface is applied to address the variation in the illumination of the image. Experiments are shown using the AR Face and ORL databases.