Gradient-based fusion of infrared and visual face images using support vector machine for human face identification

Priya Saha; Mrinal K. Bhowmik; Debotosh Bhattacharjee; Barin K. De; Mita Nasipuri

doi:10.1117/12.2001976

7 March 2013 Gradient-based fusion of infrared and visual face images using support vector machine for human face identification

Priya Saha, Mrinal K. Bhowmik, Debotosh Bhattacharjee, Barin K. De, Mita Nasipuri

Author Affiliations +

Proceedings Volume 8667, Multimedia Content and Mobile Devices; 86670Z (2013) https://doi.org/10.1117/12.2001976
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

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.

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Priya Saha, Mrinal K. Bhowmik, Debotosh Bhattacharjee, Barin K. De, and Mita Nasipuri "Gradient-based fusion of infrared and visual face images using support vector machine for human face identification", Proc. SPIE 8667, Multimedia Content and Mobile Devices, 86670Z (7 March 2013); https://doi.org/10.1117/12.2001976

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KEYWORDS

Image fusion

Independent component analysis

Visualization

Infrared imaging

Facial recognition systems

Thermography

Databases

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