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2DPCA fractal features and genetic algorithm for efficient face representation and recognition

Yousra Ben Jemaa*, Ahmed Derbel and Ahmed Ben Jmaa

Author Affiliations

Signals and Systems Unit, National Engineering School of Sfax, Sfax University, BP W 3038, Sfax, Tunisia

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EURASIP Journal on Information Security 2011, 2011:1  doi:10.1186/1687-417X-2011-1

Published: 23 August 2011


In this article, we present an automatic face recognition system. We show that fractal features obtained from Iterated Function System allow a successful face recognition and outperform the classical approaches. We propose a new fractal feature extraction algorithm based on genetic algorithms to speed up the feature extraction step. In order to capture the more important information that is contained in a face with a few fractal features, we use a bi-dimensional principal component analysis. We have shown with experimental results using two databases as to how the optimal recognition ratio and the recognition time make our system an effective tool for automatic face recognition.

face recognition; fractal coding; 2DPCA; IFS; genetic algorithms