• DocumentCode
    3203784
  • Title

    Complex background subtraction for biometric identification

  • Author

    Khalifa, A. ; Sundaraj, K. ; Ibrahim, Z. ; Retnasamy, V.

  • Author_Institution
    Sch. of Mechatron. Eng., Univ. Malaysia Perlis, Jejawi
  • fYear
    2007
  • fDate
    25-28 Nov. 2007
  • Firstpage
    696
  • Lastpage
    701
  • Abstract
    The background subtraction algorithm based on the YUV color space, image gradient and shape segmentation is used in this research to extract the region of interest from a real-time video surveillance camera. We choose to extract a human face from video sequence. This research has long been considered as an important and still challenging issue in video surveillance. In this paper we present an improved approach for detection and extraction of human face from a 2D color image. Our method produces the ellipse that contains the face, eyes and mouth which are required for face recognition. We find that this technique might be an interesting alternative for biometric identification, public face image database management, video conferencing, intelligent human computer interface and face recognition.
  • Keywords
    biometrics (access control); face recognition; feature extraction; image colour analysis; image segmentation; image sequences; video cameras; video surveillance; YUV color space; background subtraction; biometric identification; face recognition; human face detection; human face extraction; image color; image gradient; real-time video surveillance camera; shape segmentation; video sequence; Biometrics; Cameras; Color; Face detection; Face recognition; Humans; Image segmentation; Shape; Video sequences; Video surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-1355-3
  • Electronic_ISBN
    978-1-4244-1356-0
  • Type

    conf

  • DOI
    10.1109/ICIAS.2007.4658477
  • Filename
    4658477