International Journal of Mineral Processing and Extractive Metallurgy

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Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach

Received: May 17, 2017    Accepted: Jun. 12, 2017    Published: Jul. 25, 2017
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Abstract

The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox.

DOI 10.11648/j.ijmpem.20170202.11
Published in International Journal of Mineral Processing and Extractive Metallurgy ( Volume 2, Issue 2, March 2017 )
Page(s) 13-20
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Biometrics, Multibiometrics, Left and Right Palmprint Image, Feature Extraction, Discrete Wavelet Packet Transform (DWPT)

References
[1] A. K. Jain, A. Ross, and S. Prabhakar, “An introduction to biometric recognition”, IEEE Trans. Circuits Syst. Video Technol., vol. 14, no. 1, pp. 4–20, Jan. 2004.
[2] Z. Sun, T. Tan, Y. Wang, and S. Z. Li, “Ordinal palmprint represention for personal identification [represention read representation],” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., vol. 1, pp. 279–284, Jun. 2005.
[3] D. Zhang, Z. Guo, G. Lu, D. Zhang, and W. Zuo, “An online system of multispectral palmprint verification”, IEEE Trans. Instrum. Meas., vol. 59, no. 2, pp. 480–490, Feb. 2010.
[4] A. K. Jain and J. Feng, “Latent palmprint matching”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 6, pp. 1032–1047, Jun. 2009.
[5] J. Rama, and P. Malathi, “A study on unimodal and multimodal Biometrics for a person identification”, Image processing and pattern recognition, pp. 36-40, 2015.
[6] D. Zhang, W.-K. Kong, J. You, and M. Wong, “Online palmprint identification”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 9, pp. 1041–1050, Sep. 2003.
[7] S. Ribaric and I. Fratric, “A biometric identification system based on eigenpalm and eigenfinger features”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 11, pp. 1698–1709, Nov. 2005.
[8] Rajkumar Mehar, “Fuzzy Logic Approach for Person Authentication Based on Palm-print”, Transaction on Machine Learning and Artificial Intelligence, vol. 2, Issue 4, Aug. 2014.
[9] Y. Xu, D. Zhang, and L. Fei, “Combining left and right palmprint images for more accurate personal identification”, IEEE transactions on Image processing, vol. 24, no. 2, pp. 549–559, Feb. 2015.
[10] Dr. Raja Murali Prasad, “Highly Secured Bio-Metric Authentication Model with Palm Print Identification”, Int. Journal of Engineering Research and Application, vol. 6, pp. 19-24, April 2016.
[11] K. Y. Rajput, “Palmprint Recognition Using Image Processing”, International Journal of Computing Science and Communication Technologies, vol. 3, no. 2, pp. 618-621, Jan. 2011.
[12] Sincy John, “Palmprint Identification Based on Adaptive Neuro Fuzzy Inference System”, International Journal for Research In Appled Science and Engineering Technology (IJRASET), vol. 2, pp. 138-142, March 2014.
[13] IITD Touchless Palmprint Database. Version 1.0 (available online): http://web.iitd.ac.in/~ajaykr/Database_Palm”.htm. http://www4.comp.polyu.edu.hk/~csajaykr/IITD/Database_Palm.htm.
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  • APA Style

    Komal Kashyap, Ekta Tamrakar. (2017). Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach. International Journal of Mineral Processing and Extractive Metallurgy, 2(2), 13-20. https://doi.org/10.11648/j.ijmpem.20170202.11

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    ACS Style

    Komal Kashyap; Ekta Tamrakar. Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach. Int. J. Miner. Process. Extr. Metall. 2017, 2(2), 13-20. doi: 10.11648/j.ijmpem.20170202.11

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    AMA Style

    Komal Kashyap, Ekta Tamrakar. Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach. Int J Miner Process Extr Metall. 2017;2(2):13-20. doi: 10.11648/j.ijmpem.20170202.11

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  • @article{10.11648/j.ijmpem.20170202.11,
      author = {Komal Kashyap and Ekta Tamrakar},
      title = {Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach},
      journal = {International Journal of Mineral Processing and Extractive Metallurgy},
      volume = {2},
      number = {2},
      pages = {13-20},
      doi = {10.11648/j.ijmpem.20170202.11},
      url = {https://doi.org/10.11648/j.ijmpem.20170202.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijmpem.20170202.11},
      abstract = {The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox.},
     year = {2017}
    }
    

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    T1  - Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach
    AU  - Komal Kashyap
    AU  - Ekta Tamrakar
    Y1  - 2017/07/25
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    DO  - 10.11648/j.ijmpem.20170202.11
    T2  - International Journal of Mineral Processing and Extractive Metallurgy
    JF  - International Journal of Mineral Processing and Extractive Metallurgy
    JO  - International Journal of Mineral Processing and Extractive Metallurgy
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    EP  - 20
    PB  - Science Publishing Group
    SN  - 2575-1859
    UR  - https://doi.org/10.11648/j.ijmpem.20170202.11
    AB  - The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox.
    VL  - 2
    IS  - 2
    ER  - 

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Author Information
  • Department of Electronics & Telecommunication Engineering, Bhilai Institute of Technology Durg, Chhattisgarh, India

  • Department of Electronics & Telecommunication Engineering, Bhilai Institute of Technology Durg, Chhattisgarh, India

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