Face Identification based Bio-Inspired Algorithms
Journal: The International Arab Journal of Information Technology (Vol.17, No. 1)Publication Date: 2020-01-01
Authors : Sanaa Ghouzali; Souad Larabi;
Page : 118-127
Keywords : Support vector machine; projection pursuit; particle swarm optimization; genetic algorithms; Kurtosis index; Friedman index.;
Abstract
Most biometric identification applications suffer from the curse of dimensionality as the database size becomes very large, which could negatively affect both the identification performance and speed. In this paper, we use Projection Pursuit (PP) methods to determine clusters of individuals. Support Vector Machine (SVM) classifiers are then applied on each cluster of users separately. PP clustering is conducted using Friedman and Kurtosis projection indices optimized by Genetic Algorithm and Particle Swarm Optimization methods. Experimental results obtained using YALE face database showed improvement in the performance and speed of face identification system.
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Last modified: 2020-02-20 22:32:52