• DocumentCode
    3267536
  • Title

    Edge Detection Algorithm for Uneven Lighting Image Based on Vision Theory

  • Author

    Lei Zhou ; Gang Hua ; Dongmei Xu ; Haitao Wu

  • Author_Institution
    Sch. of Inf. & Electr. Eng., Univ. of Min. & Technol., Xu Zhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    182
  • Lastpage
    185
  • Abstract
    Many commonly used differential operators for edge detection which are effective and efficient on simple images canpsilat deal with relatively complex images. This paper put forward an edge detection algorithm for uneven lighting image based on vision theory. Firstly this paper introduces this vision theory, and established an effective computation model, through the preprocessing and threshold correction, the probability of losing edge at dark region and edge redundancy at bright region is reduced. At last, the algorithm based on modified Canny operator is given. Experiments indicated that this method, which is adaptive to complex image, has excellent brightness compatibility and has the ability to outstand the target. The division result is more consistent with person´s visual feeling and has built a foundation for the following recognition.
  • Keywords
    computer vision; edge detection; edge detection algorithm; image recognition; modified Canny operator; preprocessing; threshold correction; uneven lighting image; vision theory; Background noise; Brightness; Computational modeling; Computer vision; Humans; Image analysis; Image edge detection; Information analysis; Optical reflection; Video surveillance; edge detection; logarithm preprocessing; threshold correction; uneven lighting image; vision characteristic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.128
  • Filename
    5231170