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Face Recognition Based on ICA Combined with FLD

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2359))

Abstract

Recently in face recognition, as opposed to our expectation, the performance of an ICA (Independent Component Analysis) method combined with LDA (Linear Discriminant Analysis) was reported as lower than an ICA only based method. This research points out that (ICA+LDA) methods have not got a fair comparison for evaluating its recognition performance. In order to incorporate class specific information into ICA, we have employed FLD (Fisher Linear Discriminant) and have proposed our (ICA+FLD) method. In the experimental results, we report that our (ICA+FLD) method has better performance than ICA only based methods as well as other representative methods such as Eigenface and Fisherface methods.

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© 2002 Springer-Verlag Berlin Heidelberg

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Yi, J., Kim, J., Choi, J., Han, J., Lee, E. (2002). Face Recognition Based on ICA Combined with FLD. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds) Biometric Authentication. BioAW 2002. Lecture Notes in Computer Science, vol 2359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47917-1_2

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  • DOI: https://doi.org/10.1007/3-540-47917-1_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43723-9

  • Online ISBN: 978-3-540-47917-8

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