There are many applications which use Face Recognition for identification or verification of a person. In this study, a face recognition system based on HMM has been proposed to handle the problem of partial occlusion. Face is represented by eight isolated regions: Hairs, Forehead, Eyebrows, Eyes, Nose, Upper Lips, Mouth and Chin. The non-occluded region in face image of testing and training image is used for processing. Further, to increase the accuracy and robustness in the face recognition system HMM is coupled with Face Edge Length Model (FELM) in recognition phase. FELM contains various lengths between the any two edge points on the face. The proposed model is more flexible as it handles general occlusion. Experiments are performed only for sunglasses and scarf occlusions in AR database. Experimental results reveal that the proposed algorithm outperforms state-of-art as well as those methods that uses only HMM in recognition phase.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.