Information Fusion towards a Robust Face Recognition System

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As a hot research topic since the eighties, face recognition still seems to be a difficult and largely problem.

Distortions caused by variations in illumination, expression and pose are the main challenges to be dealt with by researchers in this field.

Efficient recognition algorithms, robust against such distortions, are the main motivations of this research.

Based on a detailed review on the background and wide applications of Gabor wavelet and new transforms (Contourlet, Curvelet and Steerable Pyramid) have emerged despite their improved directional elements and other promising abilities compared to traditional wavelet transform.

In this book we have introduced Steerable pyramid as a new feature extraction tool for face representation respectively recognition.

We also proposed face recognition based on multiple features fusion that combine two different representations of the face image.

We examine the impact of information fusion both at the feature level and at the score level.

Finally an automatic user identification system, is presented.

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