Face Recognition using Random Projection with Neural Network
B. Muthukumar1, S.Ravi2
1B.Muthukumar, Associate Professor, Department of Information Technology, Kathir College of Engineering, Coimbatore, Tamilnadu, India.
2Dr. S.Ravi, Professor, Department of ECE, Dr. MGR University, Chennai Tamilnadu, India.
Manuscript received on january 17, 2012. | Revised Manuscript received on February 05, 2012. | Manuscript published on February 29, 2012. | PP: 82-86 | Volume-1 Issue-3, February 2012. | Retrieval Number: C0199021312/2011©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the domain of face recognition, many methods are used to reduce the dimensionality of the subspace in which faces are presented. Recently, Random Projection (RP) has emerged as a powerful method for dimensionality reduction. It represents a computationally simple and efficient method that preserves the structure of the data without introducing very significant distortion. Our focus in this paper is to investigate the dimensionality reduction offered by RP and perform an artificial intelligent system for face recognition using back propagation neural network. Experiments show that projecting the data onto a random lower-dimensional subspace yields results and give an acceptable face recognition rate.
Keywords: Dimensionality reduction; Face Recognition, Sparse Random Projection, neural network.