STUDY AND COMPARISON OF DIFFERENT FACE RECOGNITION ALGORITHMS

Vaibhav Pathak¹, D.N. Patwari², P.B. Khanale³, N.M. Tamboli⁴, Vishal M. Pathak^5
1Shri Shivaji College, Parbhani
²Shri Shivaji College, Parbhani
³D.S.M. Parbhani
⁴M.A.U., Parbhani
⁵M.G.M’s CS & IT Parbhani

Received : -     Accepted : -     Published : 15-12-2011
Volume : 1     Issue : 1       Pages : 5 - 9
Bioinfo Med Imag 1.1 (2011):5-9

Face recognition is one of the most successful applications of image analysis and understanding and has gained much attention in recent years. Among many approaches to the problem of face recognition, appearance-based subspace analysis still gives the most promising results. In this paper we study the three most popular appearance-based face recognition projection methods (PCA, LDA and ICA). All methods are tested in equal working conditions regarding preprocessing and algorithm implementation on the FERET and AT&T data set with its standard tests. We also compare the ICA method with its whitening preprocess and find out that there is no significant difference between them. When we compare different projection with different metrics we found out that the LDA+COS combination is the most promising for all tasks. The L1 metric gives the best results in combination with PCA and ICA1, and COS is superior to any other metric when used with LDA and ICA2. Our results are compared to other studies and some discrepancies are pointed out.

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