Face recognition by multiple classifiers, a divide-and-conquer approach

Authors:
Reza Ebrahimpour;Saeed Reza Ehteram;Ehsanollah Kabir
Affiliations:
School of Cognitive Sciences, Institute for Studies on Theoretical Physics and Mathematics, Niavaran, Tehran, Iran;Department of Electrical Engineering, Pars Electric High Education Center, Jamee University of Applied, Science and Technology, Farahzad, Tehran, Iran;Department of Electrical Engineering, Tarbiat Modarres University, Tehran, Iran
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Year:
2005

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Abstract

In this paper, an approach that uses a combination of neural network classifiers (CNNC) is applied to human face recognition. We present a divide-and-conquer approach for system composed of several separate networks. Decomposing the complex problem into sub-problems for solving them by a binary base classifier is presented. Each of that learns to recognize a subject of the complete set of training database. Combining the results of sub-problems with max rule accomplished to achieve better performance. The recognition rate of 100% for ORL and Yale database was obtained using the mentioned devised algorithm.