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An effective recognition approach for contactless palmprint

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Abstract

The biometrics character has been widely used for individual identification and verification. Palmprint as one of biological features contains abundant discriminative features, which has already attracted a lot of interest. In this work, we focus on the identification and verification of contactless palmprint images. Considering the main differences between contact and contactless images, including orientation and deformation, we use a deep network combined with image alignment to further improve the recognition performance of contactless palmprint images. Recently, convolutional neural networks can well solve many classification problems, and researchers have proposed many networks with different architectures. We exploit the residual network in our framework, which achieves promising performance on the image classification problem. In order to improve the accuracy of verification, the spatial transformation network is used to align the image. The proposed method is tested on two public palmprint databases CASIA, GPDS. Extensive experiments are carried out with several state-of-the-art approaches as comparison, and the results demonstrated the effectiveness of our method.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Nos. 61501230, 61732006 and 61876082), the National Key R&D Program of China (Grant Nos. 2018YFC2001600, 2018YFC2001602), National Science and Technology Major Project (No. 2018ZX10201002), and the Fundamental Research Funds for the Central Universities (No. NJ2019010).

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Nuoya Xu, Qi Zhu, Xiangyu Xu & Daoqiang Zhang

  2. Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, 210093, China

    Nuoya Xu & Qi Zhu

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  1. Nuoya Xu
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  2. Qi Zhu
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  3. Xiangyu Xu
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  4. Daoqiang Zhang
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Correspondence to Qi Zhu.

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Xu, N., Zhu, Q., Xu, X. et al. An effective recognition approach for contactless palmprint. Vis Comput 37, 695–705 (2021). https://doi.org/10.1007/s00371-020-01962-x

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