2003 IEEE International Workshop on Computer Architectures for Machine Perception (CAMP) A COMPARATIVE STUDY OF VARIOUS FACE RECOGNITION ALGORITHMS (Feature Based, Eigen Based, Line Based, Neural Network Approaches) S.K.SinghI, Mayank Vatsa2, Richa Singh3, K.K. Shukla4 1,2,3 - Department of Computer Science & Engineering Institute of Engineering & Technology Purvanchal University, Jaunpur (U.P.) - India 4- Department of Computer Sc. & Engineering Institute of Technology - BHU (IT-BHU) Varanasi (U.P.) - India E-mail: 1 -sksiet@yahoo.com 2,3 -mayank richa@yahoo.com 4- shuklaLaieee.org Abstract As continual research is being conducted in the area of computer vision, one of the most practical applications under vigorous development is in the construction of a robust real-time face recognition system. While the problem of recognizing faces under gross variations remains largely unsolved, a demonstration system as proof of concept that such systems are now becoming practical have been developed. A system capable of reliable recognition, with reduced constraints in regards to the position and orientation of the face and the illumination and background of the image has been implemented. In this paper an attempt is made to compare existing face recognition algorithms which are widely used and subject of interest. Feature based Keywords: Face Recognition, Feature Based Approach, Eigen Face, Line Based Approach, Principal Component Analysis. Introduction Automatic human face recognition, a technique that can locate and identify human faces automatically in an image and determine "who is who" from a database, is gaining more and more attention in the area of computer vision, image processing and pattern recognition over the last two decades. There are several important steps involved in this problem: detection, representation and identification. Based on different representations, various approaches can be grouped into feature-based and image-based. In order to make this method more feasible, face images should be registered first. In 0-7803-7970-5/03/$20.00 ©2003 IEEE 160