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Normalization of Face Images Subject to Directional Illumination using Linear Model  

고재필 (연세대학교 컴퓨터학과)
김은주 (한국전산원 지식정보기술)
변혜란 (연세대학교 컴퓨터학과)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.1, 2004 , pp. 54-60 More about this Journal
Abstract
Face recognition is one of the problems to be solved by appearance based matching technique. However, the appearance of face image is very sensitive to variation in illumination. One of the easiest ways for better performance is to collect more training samples acquired under variable lightings but it is not practical in real world. ]:n object recognition, it is desirable to focus on feature extraction or normalization technique rather than focus on classifier. This paper presents a simple approach to normalization of faces subject to directional illumination. This is one of the significant issues that cause error in the face recognition process. The proposed method, ICR(illumination Compensation based on Multiple Linear Regression), is to find the plane that best fits the intensity distribution of the face image using the multiple linear regression, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experimental results show a significant improvement of the recognition accuracy.
Keywords
face normalization; illumination normalization; face preprocessing; face recognition;
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