Employing Fuzzy-Histogram Equalization to Combat Illumination Invariance in Face Recognition Systems | Zendy

Adebayo Kolawole John | Zendy; Onifade Onifade Williams | Zendy

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Employing Fuzzy-Histogram Equalization to Combat Illumination Invariance in Face Recognition Systems

Author(s) -

Adebayo Kolawole John,

Onifade Onifade Williams

Publication year - 2012

Publication title -

international journal of intelligent systems and applications

Language(s) - English

Resource type - Journals

eISSN - 2074-9058

pISSN - 2074-904X

DOI - 10.5815/ijisa.2012.09.07

Subject(s) - histogram equalization , computer science , artificial intelligence , computer vision , face (sociological concept) , pattern recognition (psychology) , equalization (audio) , adaptive histogram equalization , fuzzy logic , histogram , facial recognition system , image (mathematics) , algorithm , social science , decoding methods , sociology

with the recent surge in acceptance of face recognition systems, more and more work is needed to perfect the existing grey areas. A major concern is the issue of illumination intensities in the images used as probe and images trained in the database. This paper presents the adoption and use of fuzzy histogram equalization in combating illumination variations in face recognition systems. The face recognition algorithm used is Principal Component Analysis, PCA. Histogram equalization was enhanced using some fuzzy rules in order to get an efficient light normalization. The algorithms were implemented and tested exhaustively with and without the application of fuzzy histogram equalization to test our approach. A good and considerable result was achieved.

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