Department of Computer Science

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Feature Based Face Recognition Using Slopes
(International Conference on Control, Automation and Information Sciences, Gwangju, Korea, 2014) Isra Anwar; Shah Nawaz; Ghulam Kibria; Farooq Ali, Syed; Tahir Hassan; Jeong-Bae Kim
Face recognition from an image is a popular problem in biometrics research. In the last decade, a lot of research has been done in this area. The advantage of face based identification over other biometrics is its wide acceptability as it does not require any keys, tokens, smart cards, PINs, plastic cards or passwords etc. In this work, face recognition has been done using several feature based approaches. Two new methods are presented in which simple yet useful new features are proposed and evaluated. The main contribution of this paper is usage of a slope table along with other features for face recognition. The slopes of different fiducial points of facial components (left eye, right eye, nose and lips) are computed to fill the slope table. These two methods are compared with the existing approaches based on popular features like principal components and ratios of facial components. The results show that our proposed methods Out perform these existing approaches.