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Proceedings Paper

Gradient-based fusion of infrared and visual face images using support vector machine for human face identification
Author(s): Priya Saha; Mrinal K. Bhowmik; Debotosh Bhattacharjee; Barin K. De; Mita Nasipuri
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Paper Abstract

Pose and illumination invariant face recognition problem is now-a-days an emergent problem in the field of information security. In this paper, gradient based fusion method of gradient visual and corresponding infrared face images have been proposed to overcome the problem of illumination varying conditions. This technique mainly extracts illumination insensitive features under different conditions for effective face recognition purpose. The gradient image is computed from a visible light image. Information fusion is performed in the gradient map domain. The image fusion of infrared image and corresponding visual gradient image is done in wavelet domain by taking the maximum information of approximation and detailed coefficients. These fused images have been taken for dimension reduction using Independent Component Analysis (ICA). The reduced face images are taken for training and testing purposes from different classes of different datasets of IRIS face database. SVM multiclass strategy ‘one-vs.-all’ have been taken in the experiment. For training support vector machine, Sequential Minimal Optimization (SMO) algorithm has been used. Linear kernel and Polynomial kernel with degree 3 are used in SVM kernel functions. The experiment results show that the proposed approach generates good classification accuracies for the face images under different lighting conditions.

Paper Details

Date Published: 7 March 2013
PDF: 8 pages
Proc. SPIE 8667, Multimedia Content and Mobile Devices, 86670Z (7 March 2013); doi: 10.1117/12.2001976
Show Author Affiliations
Priya Saha, Tripura Univ. (India)
Mrinal K. Bhowmik, Tripura Univ. (India)
Debotosh Bhattacharjee, Jadavpur Univ. (India)
Barin K. De, Tripura Univ. (India)
Mita Nasipuri, Jadavpur Univ. (India)


Published in SPIE Proceedings Vol. 8667:
Multimedia Content and Mobile Devices
Dietmar Wüller; Kevin J. Matherson; Reiner Creutzburg; David Akopian; Todor G. Georgiev; Andrew Lumsdaine; Cees G. M. Snoek; Lyndon S. Kennedy, Editor(s)

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