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Palmprint Recognition Using Polynomial Neural Network

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6064))

Abstract

In this paper, we propose a robust palmprint recognition approach. Firstly, a salient-point based method is applied to segment as well as align the region of interest (ROI) from the palmprint image. Then, a subspace projection technique, namely, independent component analysis (ICA) is performed on the ROI to extract features. Finally, a polynomial neural network (PNN) is used to make classification on reduced feature subspace. The effectiveness of the proposed method has been demonstrated in experiments.

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© 2010 Springer-Verlag Berlin Heidelberg

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Huang, L., Li, N. (2010). Palmprint Recognition Using Polynomial Neural Network. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13318-3_27

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  • DOI: https://doi.org/10.1007/978-3-642-13318-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13317-6

  • Online ISBN: 978-3-642-13318-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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