Abstract
This paper presents a face recognition algorithm by using Gabor wavelet transform for facial features extraction and Support Vector Machines (SVM) for face recognition, Gabor wavelets coefficients are used to represent local facial features. The implementations of our algorithm are as follows: Firstly, facial feature points are located roughly by using a set of node templates. Secondly, Gabor wavelet coefficients are extracted at every facial feature point, and all the Gabor wavelet coefficients are catenated to represent a face image. Lastly, SVM classifiers are used for face recognition. The experimental results demonstrate the effectiveness of our face recognition algorithm.
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© 2005 Springer-Verlag Berlin Heidelberg
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Li, Y., Ou, Z., Wang, G. (2005). Face Recognition Using Gabor Features and Support Vector Machines. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_20
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DOI: https://doi.org/10.1007/11539117_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
Online ISBN: 978-3-540-31858-3
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