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Optimization of Color Conversion for Face Recognition

This paper concerns the conversion of color images to monochromatic form for the purpose of human face recognition. Many face recognition systems operate using monochromatic information alone even when color images are available. In such cases, simple color transformations are commonly used that are...

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Bibliographic Details
Published in:EURASIP journal on advances in signal processing 2004-04, Vol.2004 (4), p.948790, Article 948790
Main Authors: Jones, Creed F., Abbott, A. Lynn
Format: Article
Language:English
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Summary:This paper concerns the conversion of color images to monochromatic form for the purpose of human face recognition. Many face recognition systems operate using monochromatic information alone even when color images are available. In such cases, simple color transformations are commonly used that are not optimal for the face recognition task. We present a framework for selecting the transformation from face imagery using one of three methods: Karhunen-Loève analysis, linear regression of color distribution, and a genetic algorithm. Experimental results are presented for both the well-known eigenface method and for extraction of Gabor-based face features to demonstrate the potential for improved overall system performance. Using a database of 280 images, our experiments using these methods resulted in performance improvements of approximately 4% to 14%.
ISSN:1687-6180
1687-6172
1687-6180
DOI:10.1155/S1110865704401073