Adaptive normalization based highly efficient face recognition under uneven environments

Authors:
Phill Kyu Rhee;InJa Jeon;EunSung Jeong
Affiliations:
Dept. Of Computer Science & Engineering, Inha Univ., Incheon, South Korea;Dept. Of Computer Science & Engineering, Inha Univ., Incheon, South Korea;Dept. Of Computer Science & Engineering, Inha Univ., Incheon, South Korea
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

We present an adaptive normalization method based robust face recognition which is sufficiently insensitive to such illumination variations. The proposed method takes advantage of the concept of situation-aware construction and classifier fusion. Most previous face recognition schemes define their system structures at their design phases, and the structures are not adaptive during run-time. The proposed scheme can adapt itself to changing environment illumination by situational awareness. It processes the adaptive local histogram equalization, generates an adaptive feature vectors for constructing multiple classifiers in accordance with the identified illumination condition. The superiority of the proposed system is shown using 'Yale dataset B', IT Lab., FERET fafb database, where face images are exposed to wide range of illumination variation.