• DocumentCode
    48552
  • Title

    Distal-Interphalangeal-Crease-Based User Authentication System

  • Author

    Feng Liu ; Zhang, Dejing ; Zhenhua Guo

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
  • Volume
    8
  • Issue
    9
  • fYear
    2013
  • fDate
    Sept. 2013
  • Firstpage
    1446
  • Lastpage
    1455
  • Abstract
    Touchless-based fingerprint recognition technology is thought to be an alternative to touch-based systems to solve problems of hygienic, latent fingerprints, and maintenance. However, there are few studies about touchless fingerprint recognition systems due to the lack of a large database and the intrinsic drawback of low ridge-valley contrast of touchless fingerprint images. This paper proposes an end-to-end solution for user authentication systems based on touchless fingerprint images in which a multiview strategy is adopted to collect images and the robust fingerprint feature of touchless image is extracted for matching with high recognition accuracy. More specifically, a touchless multiview fingerprint capture device is designed to generate three views of raw images followed by preprocessing steps including region of interest (ROI) extraction and image correction. The distal interphalangeal crease (DIP)-based feature is then extracted and matched to recognize the human´s identity in which part selection is introduced to improve matching efficiency. Experiments are conducted on two sessions of touchless multiview fingerprint image database with 541 fingers acquired about two weeks apart. An EER of ~ 1.7% can be achieved by using the proposed DIP-based feature, which is much better than touchless fingerprint recognition by using scale invariant feature transformation (SIFT) and minutiae features. The given fusion results show that it is effective to combine the DIP-based feature, minutiae, and SIFT feature for touchless fingerprint recognition systems. The EER is as low as ~ 0.5%.
  • Keywords
    feature extraction; fingerprint identification; image matching; transforms; DIP-based feature; EER; ROI extraction; SIFT feature; distal-interphalangeal-crease-based feature; fingerprint feature extraction; human identity recognition; image correction; matching efficiency; minutiae features; part selection; region of interest; scale invariant feature transformation; touchless fingerprint images; touchless fingerprint recognition; touchless multiview fingerprint capture device; user authentication systems; Databases; Electronics packaging; Feature extraction; Fingerprint recognition; Image matching; Thumb; Competitive coding scheme; distal interphalangeal crease (DIP); finger width; multiview images; touchless fingerprint recognition;
  • fLanguage
    English
  • Journal_Title
    Information Forensics and Security, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1556-6013
  • Type

    jour

  • DOI
    10.1109/TIFS.2013.2272787
  • Filename
    6563102