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Proceedings Paper

Most information feature extraction (MIFE) approach for face recognition
Author(s): Jiali Zhao; Haibing Ren; Haitao Wang; Seokcheol Kee
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Paper Abstract

We present a MIFE (Most Information Feature Extraction) approach, which extract as abundant as possible information for the face classification task. In the MIFE approach, a facial image is separated into sub-regions and each sub-region makes individual’s contribution for performing face recognition. Specifically, each sub-region is subjected to a sub-region based adaptive gamma (SadaGamma) correction or sub-region based histogram equalization (SHE) in order to account for different illuminations and expressions. Experiment results show that the proposed SadaGamma/SHE correction approach provides an efficient delighting solution for face recognition. MIFE and SadaGamma/SHE correction together achieves lower error ratio in face recognition under different illumination and expression.

Paper Details

Date Published: 28 March 2005
PDF: 9 pages
Proc. SPIE 5779, Biometric Technology for Human Identification II, (28 March 2005); doi: 10.1117/12.601880
Show Author Affiliations
Jiali Zhao, Samsung Advanced Institute of Technology (China)
Institute of Automation, CAS (China)
Haibing Ren, Samsung Advanced Institute of Technology (China)
Institute of Automation, CAS (China)
Haitao Wang, Samsung Advanced Institute of Technology (China)
Institute of Automation, CAS (China)
Seokcheol Kee, Samsung Advanced Institute of Technology (South Korea)


Published in SPIE Proceedings Vol. 5779:
Biometric Technology for Human Identification II
Anil K. Jain; Nalini K. Ratha, Editor(s)

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