• DocumentCode
    2638388
  • Title

    The Research on Offline Palmprint Identification

  • Author

    Li, Jiyi ; Shi, Guangshun ; Zheng, Yan ; Liu, Yuanfang

  • Author_Institution
    Inst. of Machine Intell., Nankai Univ., Tianjin, China
  • Volume
    1
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    587
  • Lastpage
    590
  • Abstract
    This paper summarizes and integrates the approaches in our previous works. It proposes a complete system and provides a complete minutiae-based solution for the offline palmprint identification. The improved image preprocessing approach transforms the gray-scale offline palmprint images into skeleton images with the palmprint segmentation, image enhancement and thinning algorithms. The novel matching approach is a multi-phases minutiae matching based on both of the local structure and global feature. To construct a complete identification, this paper also introduces the extraction and postprocessing approaches that extract and purify the feature in this system. The experimental results reveal that the system proposed is effective and efficient for the practical application.
  • Keywords
    biometrics (access control); feature extraction; image enhancement; image matching; image segmentation; image thinning; biometrics; complete minutiae-based solution; feature extraction; gray-scale offline palmprint image; image enhancement algorithm; image preprocessing approach; image thinning algorithm; multiphase minutiae matching; offline palmprint identification; palmprint segmentation; skeleton image; Biometrics; Data preprocessing; Feature extraction; Fingerprint recognition; Gray-scale; Image databases; Image enhancement; Image quality; Skeleton; Spatial databases; Feature Extraction and Postprocessing; Feature Matching; Identification System; Image Processing; Offline Palmprint;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.548
  • Filename
    5171239