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Proceedings Paper

Image quality-based adaptive illumination normalisation for face recognition
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Paper Abstract

Automatic face recognition is a challenging task due to intra-class variations. Changes in lighting conditions during enrolment and identification stages contribute significantly to these intra-class variations. A common approach to address the effects such of varying conditions is to pre-process the biometric samples in order normalise intra-class variations. Histogram equalisation is a widely used illumination normalisation technique in face recognition. However, a recent study has shown that applying histogram equalisation on well-lit face images could lead to a decrease in recognition accuracy. This paper presents a dynamic approach to illumination normalisation, based on face image quality. The quality of a given face image is measured in terms of its luminance distortion by comparing this image against a known reference face image. Histogram equalisation is applied to a probe image if its luminance distortion is higher than a predefined threshold. We tested the proposed adaptive illumination normalisation method on the widely used Extended Yale Face Database B. Identification results demonstrate that our adaptive normalisation produces better identification accuracy compared to the conventional approach where every image is normalised, irrespective of the lighting condition they were acquired.

Paper Details

Date Published: 5 May 2009
PDF: 12 pages
Proc. SPIE 7306, Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI, 73061V (5 May 2009); doi: 10.1117/12.819087
Show Author Affiliations
Harin Sellahewa, Univ. of Buckingham (United Kingdom)
Sabah A. Jassim, Univ. of Buckingham (United Kingdom)

Published in SPIE Proceedings Vol. 7306:
Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI
B.V.K. Vijaya Kumar; Craig S. Halvorson; Šárka O. Southern; Salil Prabhakar; Arun A. Ross, Editor(s)

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