Title: A novel optimised face recognition application based on modified shuffled frog leaping algorithm

Authors: Ghada Torkhani; Anis Ladgham; Anis Sakly; Mohamed Nejib Mansouri

Addresses: Industrial Systems Study and Renewable Energy (ESIER), National Engineering School of Monastir (ENIM), University of Monastir, Tunisia; Laboratory EμE, Faculty of Sciences of Monastir (FSM), University of Monastir, Tunisia ' Laboratory EμE, Faculty of Sciences of Monastir (FSM), University of Monastir, Tunisia ' Industrial Systems Study and Renewable Energy (ESIER), National Engineering School of Monastir (ENIM), University of Monastir, Tunisia; Department of Electrical Engineering, National Engineering School of Monastir (ENIM), University of Monastir, Tunisia ' Laboratory EμE, Faculty of Sciences of Monastir (FSM), University of Monastir, Tunisia; Department of Electrical Engineering, National Engineering School of Monastir (ENIM), University of Monastir, Tunisia

Abstract: In this work, we bring to light a novel face recognition (FR) system based on modified shuffled frog leaping algorithm (MSFLA) blended to Gabor wavelets. This new approach operates straightly on feature extraction and selection stages by providing the most propitious Gabor representations of a face image. While many researchers are seeking to find better parameterisation for Gabor filters, we introduce our evolutionary MSFLA-Gabor prototype combined to support vector machine (SVM) classifier as a robust contribution in the face biometric field. Primarily, we start by highlighting the impressive quality insured by Gabor filters in salient point extraction. Next, we present the potential dynamism of metaheuristic MSFLA in enhancing feature selection as well as up grading SVM classifier performance. Then, our optimised MSFLA-Gabor-SVM algorithm is tested on three databases under varied facial expressions, illuminations and poses. The experimental results have shown higher recognition rates and lower computational complexity scores than previous techniques.

Keywords: face recognition; modified SLFA; MSFLA optimisation; memplexes; optimal solution; Gabor wavelets; Gabor representation; salient points; feature extraction; feature selection; support vector machines; SVM classification; recognition rate; biometrics; shuffled frog leaping algorithm; metaheuristics.

DOI: 10.1504/IJAPR.2017.082653

International Journal of Applied Pattern Recognition, 2017 Vol.4 No.1, pp.27 - 43

Received: 21 May 2016
Accepted: 12 Aug 2016
Published online: 04 Mar 2017 *

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