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Palmprint and Finger-Knuckle-Print for efficient person recognition based on Log-Gabor filter response

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Abstract

Person recognition systems based on biometrics are being increasingly utilized in any applications to enhance the security of physical and logical access systems. A number of biometric traits exist and are in use in various applications. Each biometric trait has its strengths and weaknesses, and the choice depends on the application. Palmprint is one of the relatively new biometrics due to its stable and unique characteristics. The rich texture information of palmprint offers one of the powerful means in person recognition. An important issue in palmprint recognition is to extract features that can discriminate an individual from the other. Recently, a novel hand-based biometric feature, Finger-Knuckle-Print (FKP), has attracted an increasing amount of attention. Like any other biometric identifiers, FKPs are believed to have the critical properties of universality, uniqueness and permanence for person recognition. In this paper, we propose a multiple traits system for person recognition using palmprint and FKP. We have used 1D Log-Gabor response to extract the information from these two traits. So, each trait is represented by the real and the imaginary templates. Such extracted templates are compared with those of the database using the Hamming distance. Using the Hong Kong Polytechnic University (PolyU) database, the experimental results showed that the proposed system achieves excellent performances in terms of computation cost and of recognition rates, for both verification and identification.

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Authors and Affiliations

  1. Signal and Image Processing Laboratory, Telecommunication Department, Electronics and Computer Science Faculty, University of Science and Technology of Houari Boumedienne, Algiers, Algeria

    Abdallah Meraoumia & Salim Chitroub

  2. Department of Computer Science, King Saud University, P.O. Box 2454, Riyadh, 11451, Saudi Arabia

    Ahmed Bouridane

  3. School of Computing, Engineering and Information Sciences, Northumbria University, Pandon Building, Newcastle upon Tyne, UK

    Ahmed Bouridane

Authors
  1. Abdallah Meraoumia
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  2. Salim Chitroub
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  3. Ahmed Bouridane
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Correspondence to Salim Chitroub.

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Meraoumia, A., Chitroub, S. & Bouridane, A. Palmprint and Finger-Knuckle-Print for efficient person recognition based on Log-Gabor filter response. Analog Integr Circ Sig Process 69, 17–27 (2011). https://doi.org/10.1007/s10470-011-9632-7

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  • DOI: https://doi.org/10.1007/s10470-011-9632-7

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