Employing Fuzzy-Histogram Equalization to Combat Illumination Invariance in Face Recognition Systems
Автор: Adebayo Kolawole John, Onifade Onifade Williams
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 9 vol.4, 2012 года.
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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.
Principal component analysis, Fuzzy Histogram Equalization, Biometric, Face recognition, Illumination Invariance
Короткий адрес: https://sciup.org/15010306
IDR: 15010306
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