Optimized Gabor Features For Facial Recognition System

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dc.contributor.authorAro, Taye Oladele
dc.contributor.authorAbikoye, Oluwakemi Christiana
dc.contributor.authorBajeh, Amos Orenyi
dc.date.accessioned2018-12-07T12:28:55Z
dc.date.available2018-12-07T12:28:55Z
dc.date.issued2018
dc.description.abstractFeature extraction is a significant process in any pattern recognition, computer vision and image processing. Among several feature extraction techniques like Fisher Linear Discriminant Analysis (FLDA), Principal Component Analysis (PCA), Elastic Bunch Graph Matching (EBGM) and Local Binary Pattern (LBP), Gabor-filters possess the ability of obtaining multi-orientation features from a facial image at several scales with the derived information being of local nature. Its optimal functionality in facial recognition is linked to its biological importance (similarity to the receptive fields of simple cells in primary visual cortex) and computational properties (optimal for calculating local spatial frequencies). Despite all the outstanding properties of Gabor-filters, this technique suffers high feature dimensionality. This paper addresses the problem of high feature dimensionality by application of Ant Colony Optimization meta-heuristic algorithm for feature selection of relevant and optimal features. Two face image databases; Olivetti Research Laboratory (ORL) Database and Locally Acquired Face Image Database (LAFI) are used to evaluate the performance of the proposed facial recognition model. The final experimental results showed better performance.en_US
dc.identifier.citationAro, T.O., Abikoye, O.C. & Bajeh, A.O. (2018): Optimized Gabor Features for Facial Recognition System. The University of Pitesti Scientific Bulletin, Series: Electronics and Computers Science, 18(1); 15-26, Published by Editura Universitatii din Pitesti.en_US
dc.identifier.issn2344 – 2158
dc.identifier.urihttp://hdl.handle.net/123456789/1363
dc.language.isoenen_US
dc.publisherEditura Universitatii din Pitestien_US
dc.subjectGabor-filtersen_US
dc.subjectfeature extractionen_US
dc.subjectpattern recognitionen_US
dc.subjectvisual cortexen_US
dc.subjectGabor featuresen_US
dc.titleOptimized Gabor Features For Facial Recognition Systemen_US
dc.typeArticleen_US

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