• DocumentCode
    724014
  • Title

    Edge detection using matched filter

  • Author

    Luo Hai-bo ; Jiao An-bo ; Xu Ling-yun ; Shao Chun-yan

  • Author_Institution
    Shenyang Inst. of Autom., Shenyang, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    1132
  • Lastpage
    1136
  • Abstract
    For target tracking, automatic target recognition and detection applications, they value edge detection sensibility, precision and location accuracy rather than other criterions. Aimed at these three criterions, this paper presents an edge detection algorithm based on matched filter. Firstly, a matched filter was designed by analyzing the edge model for natural image, then the edge response was computed using the designed matched filter; secondly, the lower and discontinuous filtered responses were further suppressed using a dedicated one-dimension filter; finally, the edge image was obtained by binarizing the edge response with a local adaptive threshold. Experimental results illustrate that the proposed algorithm has more improvement than the Sobel and Canny operators in detection sensibility, precision and location accuracy. Moreover, the algorithm can be implemented with parallel pipeline using FPGA, so it is also rather suitable for real-time applications.
  • Keywords
    edge detection; field programmable gate arrays; image segmentation; matched filters; object recognition; target tracking; Canny operator; FPGA; Sobel operator; automatic target recognition; edge detection algorithm; edge model; edge response; matched filter; natural image; one-dimension filter; parallel pipeline; target tracking; Feature extraction; Filtering theory; Finite impulse response filters; Image edge detection; Matched filters; Mathematical model; Noise; edge detection; local adaptive threshold; matched filter; noise suppression; real-time application;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7162087
  • Filename
    7162087