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Palmprint Recognition Using Gabor Feature-Based Bidirectional 2DLDA

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Computer Science for Environmental Engineering and EcoInformatics (CSEEE 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 159))

Abstract

A procedure for palmprint recognition and a novel fusion strategy are proposed in this paper. The procedure is based on a combination of Gabor filters and bidirectional two dimensional linear discriminant analysis’ (2DLDA) fusion. We apply horizontal 2DLDA (H2DLDA or 2DLDA) and vertical 2DLDA (V2DLDA) to extract two kinds of features of Gabor-based images (Gaborpalms): one kind is composed of horizontal discriminant features mainly extracted by 2DLDA, and the other is composed of the vertical features extracted by V2DLDA. To fuse these two kinds of features together, a distance-based adaptive strategy is designed. Finally the nearest neighbor classifier is used for classification. Using the Gaborpalms of a little higher dimension which means low computational cost, experimental results on PolyU Palmprint Database demonstrate that the proposed procedure delivers several desired results.

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© 2011 Springer-Verlag Berlin Heidelberg

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Du, F., Yu, P., Li, H., Zhu, L. (2011). Palmprint Recognition Using Gabor Feature-Based Bidirectional 2DLDA. In: Yu, Y., Yu, Z., Zhao, J. (eds) Computer Science for Environmental Engineering and EcoInformatics. CSEEE 2011. Communications in Computer and Information Science, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22691-5_40

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  • DOI: https://doi.org/10.1007/978-3-642-22691-5_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22690-8

  • Online ISBN: 978-3-642-22691-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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