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Illumination normalization for robust face recognition against varying lighting conditions

Shiguang Shan, Gao, Wen, Bo Cao, Debin Zhao·2003·2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443)

Abstract

Evaluations of the state-of-the-art of both academic face recognition algorithms and commercial systems have shown that recognition performance of most current technologies degrades due to the variations of illumination. We investigate several illumination normalization methods and propose some novel solutions. The main contribution includes: (1) A gamma intensity correction (GIC) method is proposed to normalize the overall image intensity at the given illumination level; (2) A region-based strategy combining GIC and the histogram equalization (HE) is proposed to further eliminate the side-lighting effect; (3) A quotient illumination relighting (QIR) method is presented to synthesize images under a predefined normal lighting condition from the provided face images captured under nonnormal lighting condition. These methods are evaluated and compared on the Yale illumination face database B and Harvard illumination face database. Considerable improvements are observed. Some conclusions are given at last.

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Metadata

Authors
Shan, S., Gao, W., Cao, B., & Zhao, D.
Venue
2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443)
Publisher
IEEE
Published
2003
Pages
157-164
ISSN
1078-621X (ISSN-L)
OpenAlex
W2155000092
Cited by
358
References
1
FWCI
6.17
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Illumination normalization for robust face recognition against varying lighting conditions. https://app.cochat.ai/papers/10.1109/amfg.2003.1240838
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Shan, S., Gao, W., Cao, B., & Zhao, D. (2003). Illumination normalization for robust face recognition against varying lighting conditions. 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443). https://doi.org/10.1109/amfg.2003.1240838

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