Abstract

"Abstract: Face recognition system should be able to automatically detect a face in images. This involves extraction of its features and then recognizes it, regardless of lighting, ageing, occlusion, expression, illumination and pose. The Singular Value Decomposition and Principal Component Analysis are very useful techniques in data analysis and visualization. Singular Value Decomposition approach used in image compression and face recognition. In this paper we have attempted a comparative study of Singular Value Decomposition. The first experiment is used standard face95 and face96 Database. The performance of SVD is 100%. The second experiment is used standard grimances database. Two different classes are tested using SVD and its performance is 100%.The experiment is also tested for locally created poor image quality database and pose variation database and its recognition performance is 100%. "

Authors and Affiliations