Face recognition with contiguous occlusion based on image segmentation

Aiming to the issue of face recognition with partial contiguous occlusion, a new face recognition method was proposed by removing the outlier area in this paper. A mean face image is firstly obtained from train images, which is subtracted by the test face to form an error face image. Then the error face image is used to obtain the occlusion area of the test image by image segmentation technique, and the train images and test image are tailored by removing the corresponding occlusion area. Finally, face recognition is performed by linear regression classifier or sparse coding classifier. Compared to the similar works, the proposed method has considerably recognition performance improvement with relatively simple computational complexity. Simulation experimental results based on the standard AR face database show effectiveness of this proposed method.