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Human identification using palm print images based on deep learning methods and gray wolf optimization algorithm

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Abstract

Palm print identification is a biometric technique that relies on the distinctive characteristics of a person’s palm print to distinguish and authenticate their identity. The unique pattern of ridges, lines, and other features present on the palm allows for the identification of an individual. The ridges and lines on the palm are formed during embryonic development and remain relatively unchanged throughout a person’s lifetime, making palm prints an ideal candidate for biometric identification. Using deep learning networks, such as GoogLeNet, SqueezeNet, and AlexNet combined with gray wolf optimization, we achieved to extract and analyze the unique features of a person’s palm print to create a digital representation that can be used for identification purposes with a high degree of accuracy. To this end, two well-known datasets, the Hong Kong Polytechnic University dataset and the Tongji Contactless dataset, were used for testing and evaluation. The recognition rate of the proposed method was compared with other existing methods such as principal component analysis, including local binary pattern and Laplacian of Gaussian-Gabor transform. The results demonstrate that the proposed method outperforms other methods with a recognition rate of 96.72%. These findings show that the combination of deep learning and gray wolf optimization can effectively improve the accuracy of human identification using palm print images.

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The datasets used in the research are publicly available for download.

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Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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Authors and Affiliations

  1. Department of Computer Engineering, Cankiri Karatekin University, Cankiri, Turkey

    Firas Alshakree

  2. Department of Computer Engineering, Abdullah Gul University, Kayseri, Turkey

    Ayhan Akbas

  3. Department of Software Engineering, Istanbul Topkapi University, Istanbul, Turkey

    Javad Rahebi

Authors
  1. Firas Alshakree
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  2. Ayhan Akbas
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  3. Javad Rahebi
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Correspondence to Ayhan Akbas.

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Alshakree, F., Akbas, A. & Rahebi, J. Human identification using palm print images based on deep learning methods and gray wolf optimization algorithm. SIViP 18, 961–973 (2024). https://doi.org/10.1007/s11760-023-02787-6

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  • DOI: https://doi.org/10.1007/s11760-023-02787-6

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