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Deformation Invariant and Contactless Palmprint Recognition Using Convolutional Neural Network

Published: 21 October 2015 Publication History

Abstract

Palmprint recognition is a challenging problem, mainly due to low quality of the patterns, variation in focal lens distance, large nonlinear deformations caused by contactless image acquisition system, and computational complexity for the large image size of typical palmprints. This paper proposes a new contactless biometric system using features of palm texture extracted from the single hand image acquired from a digital camera. In this work, we propose to apply convolutional neural network (CNN) for palmprint recognition. The results demonstrate that the extracted local and general features using CNN are invariant to image rotation, translation, and scale variations.

References

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Abukmeil, M. A., Elaydi, H., and Alhanjouri, M. Palmprint Recognitionvia Bandlet, Ridgelet, Wavelet and Neural Network. Journal of Computer Sciences and Applications 3, 2 (2015), 23--28.
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Cappelli, R., Ferrara, M., and Maio, D. A fast and accurate palmprint recognition system based on minutiae. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 42, 3 (2012), 956--962.
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Kekre, H. B., Vig, R., Bisani, S., Sarode, T., Arya, P., and Irani, A. Identification of multi-spectral palmprints using energy compaction by hybrid wavelet. In Biometrics (ICB), 2012 5th IAPR International Conference on, (2012), 433--438.
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Li, W., Zhang, D., Lu, G., and Yan, J. Efficient joint 2D and 3D palmprint matching with alignment refinement. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, (2010), 795--801.
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Lu, J., Zhang, E., Kang, X., Xue, Y., and Chen, Y. Palmprint recognition using wavelet decomposition and 2D principal component analysis. In Communications, Circuits and Systems Proceedings, 2006 International Conference on, (2006), 2133--2136.
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Morales, A., Ferrer, M. A., and Kumar, A. Improved palmprint authentication using contactless imaging. In Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on, (2010), 1--6.
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Cited By

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  • (2022)ToothSonicProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346066:2(1-24)Online publication date: 7-Jul-2022
  • (2021)EarDynamicProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34480985:1(1-27)Online publication date: 30-Mar-2021
  • (2019)Boosting palmprint identification with gender information using DeepNetFuture Generation Computer Systems10.1016/j.future.2019.04.01399:C(41-53)Online publication date: 1-Oct-2019
  • Show More Cited By

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  1. Deformation Invariant and Contactless Palmprint Recognition Using Convolutional Neural Network

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      cover image ACM Other conferences
      HAI '15: Proceedings of the 3rd International Conference on Human-Agent Interaction
      October 2015
      254 pages
      ISBN:9781450335270
      DOI:10.1145/2814940
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      • BESK: Brain Engineering Society of Korea

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 21 October 2015

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      Author Tags

      1. biometric
      2. contactless palmprint recognition
      3. convolutioanl neural network
      4. feature extraction

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      • Research-article

      Funding Sources

      • "Software Convergence Technology Program" through the Ministry of Science ICT and Future Planning

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      HAI 2015
      Sponsor:
      • BESK
      HAI 2015: The Third International Conference on Human-Agent Interaction
      October 21 - 24, 2015
      Kyungpook, Daegu, Republic of Korea

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      Overall Acceptance Rate 121 of 404 submissions, 30%

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      Cited By

      View all
      • (2022)ToothSonicProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346066:2(1-24)Online publication date: 7-Jul-2022
      • (2021)EarDynamicProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34480985:1(1-27)Online publication date: 30-Mar-2021
      • (2019)Boosting palmprint identification with gender information using DeepNetFuture Generation Computer Systems10.1016/j.future.2019.04.01399:C(41-53)Online publication date: 1-Oct-2019
      • (2018)Deep Learning for BiometricsACM Computing Surveys10.1145/319061851:3(1-34)Online publication date: 23-May-2018

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