NDLI: Illumination normalization for face recognition and uneven background correction using total variation based image models

Content Provider	IEEE Xplore Digital Library
Author	Chen, T. Yin, W. Zhou, X.S. Comaniciu, D. Huang, T.S.
Copyright Year	2005
Description	Author affiliation: Illinois Univ., Urbana, IL, USA (Chen, T.)
Abstract	We present a new algorithm for illumination normalization and uneven background correction in images, utilizing the recently proposed TV+L/sup 1/ model: minimizing the total variation of the output cartoon while subject to an L/sup 1/-norm fidelity term. We give intuitive proofs of its main advantages, including the well-known edge preserving capability, minimal signal distortion, and scale-dependent but intensity-independent foreground extraction. We then propose a novel TV-based quotient image model (TVQI) for illumination normalization, an important preprocessing for face recognition under different lighting conditions. Using this model, we achieve 100% face recognition rate on Yale face database B if the reference images are under good lighting condition and 99.45% if not. These results, compared to the average 65% recognition rate of the quotient image model and the average 95% recognition rate of the more recent self quotient image model, show a clear improvement. In addition, this model requires no training data, no assumption on the light source, and no alignment between different images for illumination normalization. We also present the results of the related applications - uneven background correction for cDNA mic roar ray films and digital microscope images. We believe the proposed works can serve important roles in the related fields.
Sponsorship	IEEE Comput. Soc
Starting Page	532
Ending Page	539
File Size	849472
Page Count	8
File Format	PDF
ISBN	0769523722
ISSN	10636919
DOI	10.1109/CVPR.2005.181
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lighting Face recognition Light sources Distortion Image recognition Microscopy Image databases Training data Surface texture Computer vision
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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