ISSN : 1796-2048
Volume : 3    Issue : 1    Date : May 2008

Dimensionality Reduction using SOM based Technique for Face Recognition
Dinesh Kumar, C.S. Rai, and Shakti Kumar
Page(s): 1-6
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Unsupervised or Self-Organized learning algorithms have become very popular for discovery of
significant patterns or features in the input data. The three prominent algorithms namely Principal
Component Analysis (PCA), Self Organizing Maps (SOM), and Independent Component Analysis
(ICA) have widely and successfully been used for face recognition. In this paper a SOM based
technique for dimensionality reduction has been proposed. This technique has also been
successfully used for face recognition. A comparative study of PCA, SOM and ICA along with the
proposed technique for face recognition has also been given. Simulation results indicate that SOM
is better than the other techniques for the given face database and the classifier used. The results
also show that the performance of the system decreases as the number of classes increase.

Index Terms
Face Recognition, Principal Component Analysis, Self-Organizing Map, Independent Component