• DocumentCode
    2564554
  • Title

    Derivative method for hand palm texture biometric verification

  • Author

    Travieso, Carlos M. ; Fuertes, Juan José ; Alonso, Jesús B.

  • Author_Institution
    Signals & Commun. Dept., Univ. de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
  • fYear
    2011
  • fDate
    18-21 Oct. 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this work, a novel, simple and very robust biometric verification system through the use of the texture of the hand palm is proposed. It attempts to make the performance of existing palm-print systems better. First of all, the hand palm image with scale, rotation and translation invariance is isolated from the hand image recorded. Then, the “derivative method” presented in this paper, is used to extract the texture features from gray-scale images. It consists of a differentiation and binarization process. 1090 hand images of 109 people with 10 samples each one have been acquired by means of a commercial scanner with 150 dpi resolution. Support Vector Machine (SVM) is the main classifier used as verifier, in closed mode and open mode. An EER=0.30% and an EER=0.032% shown the final results of our system when it works in open and closed mode respectively.
  • Keywords
    feature extraction; image classification; image texture; palmprint recognition; support vector machines; binarization process; derivative method; differentiation process; hand palm texture biometric verification system; palm-print systems; rotation invariance; scale invariance; support vector machine; texture feature extraction; translation invariance; Biomedical imaging; Feature extraction; Robustness; Support vector machines; Thumb; Vectors; Biometrics; hand verification system; palmprint texture; pattern recognition and classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Security Technology (ICCST), 2011 IEEE International Carnahan Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1071-6572
  • Print_ISBN
    978-1-4577-0902-9
  • Type

    conf

  • DOI
    10.1109/CCST.2011.6095889
  • Filename
    6095889