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Discriminative BULBPH Descriptor with KDA for Palmprint Recognition

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1022))

Abstract

This work proposes Block-wise uniform local binary pattern histogram (BULBPH) followed by kernel discrimination analysis (KDA) as descriptor for palmprint recognition. BULBPH provides distribution of uniform patterns (such as line and wrinkles) in local region and can be better used as palmprint features. KDA is applied on BULBPH to reduce dimension and enhance discriminative capability using chi-RBF kernel. The experiments are conducted on four palmprint databases and performance is compared with related descriptors. It is observed that KDA on BULBPH descriptor achieves more than 99% accuracy with 4.04 decidability index on four palmprint databases.

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Correspondence to Pritee Khanna .

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Tamrakar, D., Khanna, P. (2020). Discriminative BULBPH Descriptor with KDA for Palmprint Recognition. In: Chaudhuri, B., Nakagawa, M., Khanna, P., Kumar, S. (eds) Proceedings of 3rd International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1022. Springer, Singapore. https://doi.org/10.1007/978-981-32-9088-4_35

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  • DOI: https://doi.org/10.1007/978-981-32-9088-4_35

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  • Print ISBN: 978-981-32-9087-7

  • Online ISBN: 978-981-32-9088-4

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