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Face Recognition Using K2dDSPCA

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Executive Summary

Face recognition is one of biometric methods, to identify given face image using main features of face. In this paper, a neural based algorithm is presented, to detect frontal views of faces. The dimensionality of face image is reduced by the Kernel based 2 Dimensional Symmetrical Principal Component Analysis (K2DSPCA) and the recognition are done by the Back Propagation Neural Network (BPNN). Here 200 face images from Yale database are taken and some performance metrics like Acceptance ratio and Execution time are calculated. Neural based Face recognition is robust and has better performance of more than 90 % acceptance ratio.

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