• DocumentCode
    628103
  • Title

    Implementation of feature extraction based hand geometry in biometric identification system

  • Author

    Budi Wirayuda, Tjokorda Agung ; Kuswanto, Didik Hari ; Adhi, Habbi Ananto ; Dayawati, Retno Novi

  • Author_Institution
    Fac. of Inf., Telkom Inst. of Technol., Bandung, Indonesia
  • fYear
    2013
  • fDate
    20-22 March 2013
  • Firstpage
    259
  • Lastpage
    263
  • Abstract
    Biometric identification system is one method that aims to identify a person´s identity automatically based on biometric characteristic. Biometric characteristics may include iris, fingerprint, face, voice, or palm. Palm is one of the biometric characteristics that can be used to distinguish a person´s identity, because everyone has different palm lines, shapes and sizes. Therefore, in recent years a lot of research done related to biometric identification system based on palm. One of the main problems in the biometric identification system based on the palm is how to extract features automatically without using special devices, because it is the core of biometric identification system. Several information that can be used as the based of this system are the geometry and the lines of the palm. In this study, the palms feature extraction based on it´s geometry to find information will be examined, which includes finger width, finger length, palm width, and the ratio between the length of the middle finger, index finger and ring finger. By combining this information can be obtained a characteristic of palms that can be used to recognize a person. The accuracy obtained in this system is 88.4% using the 23 Characteristics of palm geometry without normalization and with 0.035 thresholds on 40 individuals. The characteristic that is used were the fingers length, finger width, and the width of the palm it self. In this experiment, the reduction of characteristics used has a great influent on the accuracy of the system. The test results showed the best accuracy at 35 individuals, with 90.05% accuracy.
  • Keywords
    feature extraction; fingerprint identification; palmprint recognition; biometric characteristics; biometric identification system; face; finger length; finger width; fingerprint; hand geometry; index finger; iris; middle finger; palm feature extraction; palm geometry; palm width; person identity; person recognition; ring finger; voice; Feature extraction; Geometry; Indexes; Smoothing methods; Thumb; Vectors; Biometric; Feature extraction; Identification system; Palm geometry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technology (ICoICT), 2013 International Conference of
  • Conference_Location
    Bandung
  • Print_ISBN
    978-1-4673-4990-1
  • Type

    conf

  • DOI
    10.1109/ICoICT.2013.6574583
  • Filename
    6574583