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Research Journal of Information Technology
  Year: 2009 | Volume: 1 | Issue: 1 | Page No.: 17-29
DOI: 10.3923/rjit.2009.17.29
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Frontal Colored Face Recognition System

Zouhir Wakaf and Mariam M. Saii

A system for face recognition in colored frontal face images is proposed. This study presents a new scheme for feature extraction based on deformable models and morphs using the 2D wavelet multi-resolution decomposition, then, a classical semi-parametric system of a multi layered perceptron neural network is employed for classification purpose. A heuristic is designed for defining the face only bounding rectangle thus excluding most of the facial hair, ears and neck and then we defined depending on this computed rectangle four regions of interest, representing the forehead, eye`s sockets, nose and chin regions. This heuristic also gives our system invulnerability against both translations and z-axis limited rotations. Next, 2D wavelet coefficients for the three channels of red, green and blue are computed for the whole image using the multi-resolution decomposition. A classification system of back propagation multi layered perceptron neural network is designed and trained with momentum learning and the cross validation during network training in the search procedure and the hyper tangent nonlinearity as an activation function. Our system is experimented with colored faces from the Stirling University database and the preliminary results we obtained show an 88% success rate.
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How to cite this article:

Zouhir Wakaf and Mariam M. Saii, 2009. Frontal Colored Face Recognition System. Research Journal of Information Technology, 1: 17-29.

DOI: 10.3923/rjit.2009.17.29






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