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Fuzzy-Based Classification for Fusion of Palmprint and Iris Biometric Traits

  • Akram AlsubariEmail author
  • Preeti Lonkhande
  • R. J. Ramteke
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 922)

Abstract

The fusion of palmprint and iris biometric traits is implemented in this paper. The region of interest (ROI) of palm is detected and segmented based on the valley detection algorithm and the ROI of iris is extracted based on the Neighbor-Pixels Value Algorithm (NPVA). The statistical-local binary pattern (SLBP) is used for extracting the local features from the iris and palm. For enhancing the palm features, the combination of discrete cosine transform (DCT) and histogram of oriented gradient (HOG) are applied. The Gabor–Zernike moment is used to extract the iris features. This experimentation was carried out in the identification system. The fuzzy Gaussian membership function was used as classification in the matching stage for the fusion system of palm and iris. The CASIA datasets of palm and iris were used in this research work. The proposed system accuracy was found to be satisfactory.

Keywords

Palmprint Iris Valley detection SLBP HOG DCT Zernike moment Fuzzy 

Notes

Acknowledgements

The research work is supported and sponsored by SAP DRS-II (No.: F.4-7/2018/DRS-II(SAP-II)), UGC New Delhi, India.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Akram Alsubari
    • 1
    Email author
  • Preeti Lonkhande
    • 2
  • R. J. Ramteke
    • 1
  1. 1.School of Computer SciencesKBC North Maharashtra UniversityJalgaonIndia
  2. 2.MGAH UniversityWardhaIndia

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