Intra-difference based Segmentation and Face Identification

This paper utilizes the intra-difference in still images to segment a face from its background and then combines the intra-difference detection result with the eigenface/eigenfeature methods to identify the face. This novel diverse scheme can finally solve the problem of accuracy in practical applications, thus broadening the application of face recognition into more versatile situations such as security building entrance, customs and mug spotting. The organic combination of intra-difference detection method and eigenface/eigenfeature methods into one system is shown to be more robust and have a better identification rate than either method alone. This paper first addresses the problems of the real-time accuracy issue and the need of pre-processing (mainly normalization). And then it proposes to use intra-difference to effectively segment a human face. The segmented face is further processed by both intra-difference detection method and eigenface/eigenfeature methods to determine its identity. Correspondingly, the proposed algorithm consists of three parts: segmentation, pre-processing, and multi-phase face identification by fusing the results from both the intra-difference detection method and the eigenface/eigenfeature methods.