Abstract
This paper introduces an innovative method, Dynamic Local Feature Analysis (DLFA), for human face recognition. In our proposed method, the face shape and the facial texture information are combined together by using the Local Feature Analysis (LFA) technique. The shape information is obtained by using our proposed adaptive edge detecting method that can reduce the effect on different lighting conditions, while the texture information provides the details of the normalized facial feature on the image. Finally, both the shape and texture information is combined together by means of LFA for dimension reduction. As a result, a high recognition rate is achieved no matter the face is enrolled under different or bad lighting conditions.
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© 2004 Springer-Verlag Berlin Heidelberg
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Ng, J., Cheung, H. (2004). Dynamic Local Feature Analysis for Face Recognition. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_33
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DOI: https://doi.org/10.1007/978-3-540-25948-0_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22146-3
Online ISBN: 978-3-540-25948-0
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