Face Recognition Using Bacteria Foraging Optimization-Based Selected Features
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2011, Vol 2, Issue 9
Abstract
Feature selection (FS) is a global optimization problem in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable recognition accuracy. This paper presents a novel feature selection algorithm based on Bacteria Foraging Optimization (BFO). The algorithm is applied to coefficients extracted by discrete cosine transforms (DCT). Evolution is driven by a fitness function defined in terms of maximizing the class separation (scatter index). Performance is evaluated using the ORL face database.
Authors and Affiliations
Rasleen Jakhar, Navdeep Kaur, Ramandeep Singh
Keywords
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