• DocumentCode
    1698614
  • Title

    The edge detection of river model based on self-adaptive Canny Algorithm and connected domain segmentation

  • Author

    Zhao, Jianjun ; Yu, Heng ; Gu, Xiaoguang ; Wang, Sheng

  • Author_Institution
    Inst. of Adv. Control & Intell. Inf. Process., Henan Univ., Kaifeng, China
  • fYear
    2010
  • Firstpage
    1333
  • Lastpage
    1336
  • Abstract
    An image edge detection method of river regime is presented for river model images. This method of self-adaptive thresholding Canny edge detection can extracts the edges of river regime automatically. It not only inherits the advantages of traditional Canny Algorithm, but also uses the improved maximum variance ratio method to calculate the values of Canny gradient threshold self-adaptively. And on this basis, morphological connected domain segmentation be used to suppress the interference edge of the image. This method achieves the automatic identification and extraction of river regime of the model. Tests showed that proposed algorithm has good robustness and high extraction precision, so that the next step of width measurement will be easier and preciser.
  • Keywords
    edge detection; feature extraction; image segmentation; interference suppression; rivers; connected domain; edge detection; image segmentation; interference suppression; maximum variance ratio method; river model; river regime extraction; river regime identification; self-adaptive thresholding Canny algorithm; Computational modeling; Heuristic algorithms; Histograms; Image edge detection; Image segmentation; Pixel; Rivers; Connected domain; Edge detection; Maximum variance ratio; River model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5554869
  • Filename
    5554869