Image-Quality-Based Adaptive Face Recognition

Sellahewa, Harin and Jassim, Sabah A. (2010) Image-Quality-Based Adaptive Face Recognition. IEEE Transactions on Instrumentation and Measurement, 59 (4). pp. 805-813. ISSN 0018-9456

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The accuracy of automated face recognition systems is greatly affected by intraclass variations between enrollment and identification stages. In particular, changes in lighting conditions is a major contributor to these variations. Common approaches to address the effects of varying lighting conditions include preprocessing face images to normalize intraclass variations and the use of illumination invariant face descriptors. Histogram equalization is a widely used technique in face recognition to normalize variations in illumination. However, normalizing well-lit face images could lead to a decrease in recognition accuracy. The multiresolution property of wavelet transforms is used in face recognition to extract facial feature descriptors at different scales and frequencies. The high-frequency wavelet subbands have shown to provide illumination-invariant face descriptors. However, the approximation wavelet subbands have shown to be a better feature representation for well-lit face images. Fusion of match scores from low- and high-frequency-based face representations have shown to improve recognition accuracy under varying lighting conditions. However, the selection of fusion parameters for different lighting conditions remains unsolved. Motivated by these observations, this paper presents adaptive approaches to face recognition to overcome the adverse effects of varying lighting conditions. Image quality, which is measured in terms of luminance distortion in comparison to a known reference image, will be used as the base for adapting the application of global and region illumination normalization procedures. Image quality is also used to adaptively select fusion parameters for wavelet-based multistream face recognition.

Item Type: Article
Additional Information: © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Human face Recognition (Computer science), Wavelets (Mathematics)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Harin Sellahewa
Date Deposited: 28 Jul 2015 14:45
Last Modified: 07 Jun 2016 10:10

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