• DocumentCode
    573514
  • Title

    Contactless finger knuckle identification using smartphones

  • Author

    Cheng, KamYuen ; Kumar, Ajay

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
  • fYear
    2012
  • fDate
    6-7 Sept. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper details the development of a smartphone based online system to automatically identify a person by using their finger knuckle image. The key objective is to exploit user-friendly biometric, with least privacy concern, to enhance security of the data in smartphone. The final product from this research is a finger knuckle authentication smartphone application, which is developed under Android operating system with environment version 2.3.3. This paper has developed some specialized algorithms for the finger knuckle detection, image pre-processing and region segmentation. Automatically detected and segmented finger knuckle images are used to encode finger knuckle pattern phase information using a pair of log-Gabor filters. Efficient implementation of various modules is achieved in C/C++ programming language, with OpenCV library, for online application. We also developed a user-friendly graphical user interface for the users to enroll and authenticate themselves. The developed system can therefore acquire finger knuckle image from the smartphone camera and automatically authenticate the genuine users. This paper has also developed a new smartphone based finger knuckle image database of 561 finger knuckle images of 187 different fingers from 109 users, in real imaging environment. In the best of our knowledge, this is the first attempt to develop a mobile phone based finger knuckle identification which has shown highly promising results in automatically identifying the users from their finger knuckle images.
  • Keywords
    C++ language; authorisation; biometrics (access control); data privacy; graphical user interfaces; image segmentation; object detection; operating systems (computers); smart phones; Android operating system version 2.3.3; C programming language; C++ programming language; OpenCV library; automatic person identification; contactless finger knuckle identification; data security enhancement; finger knuckle authentication smartphone application; finger knuckle detection; finger knuckle image; finger knuckle pattern phase information encoding; image pre-processing; log-Gabor filters; online system; privacy concern; region segmentation; smartphone camera; user-friendly biometric; user-friendly graphical user interface; Cameras; Feature extraction; Gabor filters; Image segmentation; Smart phones; Thumb;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics Special Interest Group (BIOSIG), 2012 BIOSIG - Proceedings of the International Conference of the
  • Conference_Location
    Darmstadt
  • ISSN
    1617-5468
  • Print_ISBN
    978-1-4673-1010-9
  • Type

    conf

  • Filename
    6313560