• DocumentCode
    3503729
  • Title

    An adaptive edge detection algorithm based on gray-scale morphology

  • Author

    Xiufang Wang ; Xingyuan Zhang ; Running Gao

  • Author_Institution
    Sch. of Electr. Eng. & Inf., Northeast Pet. Univ., Daqing, China
  • Volume
    02
  • fYear
    2013
  • fDate
    16-18 Aug. 2013
  • Firstpage
    1251
  • Lastpage
    1254
  • Abstract
    The method of image edge detection algorithm based on the traditional mathematical morphology has good ability to filter noise. But the method of using single form and single scale form element to edge the image has pertinence so the generality is weak. An algorithm of adaptive grayscale image edge detection based on multi-scale and multi-form is proposed in this paper. The image is processed with different shapes and dimensions of structural elements, and the adaptively weights are calculated according to information entropy. And we build a series-parallel form of edge detector. At last, we can get the final edge image after the fusion of each result from single element according to the series-parallel edge detector. The results of simulation show that compared with several conventional edge detection algorithms, the proposed algorithm can not only filter most of noise but also retain good edge details.
  • Keywords
    edge detection; entropy; image denoising; mathematical morphology; adaptive grayscale image edge detection algorithm; edge details; gray-scale morphology; image processing; information entropy; mathematical morphology; multiform image edge detection; multiscale image edge detection; noise filtering; series-parallel form edge detector; structural element dimension; structural element shape; Gray-scale; Image edge detection; Noise; adaptive; edge detection; grayscale morphology; multi-form; multi-scale;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measurement, Information and Control (ICMIC), 2013 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4799-1390-9
  • Type

    conf

  • DOI
    10.1109/MIC.2013.6758186
  • Filename
    6758186