Abstract
A face recognition algorithm is proposed based on Curvelet transform and Class estimated basis Space singular Value De-composition (CSVD). Face images are decomposed by using Curvelet transform firstly. As a result, Curvelet coefficients in different scales and various angels are obtained. Then, the images reconstructed by the Curvelet coefficients of the coarse layer are processed by a Fourier transform with invariant prosperity against spatial translation. CSVD algorithm is used to reduce the dimensionality and extract the feature of the amplitude spectrum face. Finally, the nearest neighbor decision rule is applied to identify the unknown face. The standard face databases of ORL, FERET and Yale are selected to evaluate the recognition accuracy of the algorithm. The results show that the proposed algorithm is used to improve the recognition rate effectively.
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© 2011 Springer-Verlag Berlin Heidelberg
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Song, S., Zhang, Y., Wang, X., Mu, X. (2011). The Face Recognition Algorithm Based on Curvelet Transform and CSVD. In: Wang, Y., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25664-6_83
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DOI: https://doi.org/10.1007/978-3-642-25664-6_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25663-9
Online ISBN: 978-3-642-25664-6
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