• DocumentCode
    1989800
  • Title

    Research on Stainless Steel Pipes Auto-Count Algorithm Based on Image Processing

  • Author

    Liu, Yu ; Liu, Yongxin ; Sun, Zhenda

  • Author_Institution
    Coll. of Electron. Inf. Eng., Inner Mongolia Univ., Hohhot, China
  • fYear
    2012
  • fDate
    27-30 May 2012
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    For solving complex stainless steel pipes auto-count problem, an algorithm is developed based on image processing. The algorithms include three sections: edge enhancement, objects extraction and pipe number count. In edge enhancement algorithm, a Canny operator combine with morphological for picking up interest area and removing noise. A novel convolution template is prompted for enhancing the thin steel pipe edge. For obtaining connected domains, an algorithm is designed by using the morphological theory. Divide each connected domain and the amount of steel pipes can be counted. Using this algorithm counting the pipe number in a real image, the 93.2% correct rate is got.
  • Keywords
    convolution; edge detection; feature extraction; image denoising; image enhancement; pipes; production engineering computing; stainless steel; steel industry; Canny operator; convolution template; image processing; morphological theory; noise removal; objects extraction; pipe number count; stainless steel pipes auto-count algorithm; thin steel pipe edge enhancement; Algorithm design and analysis; Image edge detection; Image reconstruction; Image segmentation; Noise; Steel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering and Technology (S-CET), 2012 Spring Congress on
  • Conference_Location
    Xian
  • Print_ISBN
    978-1-4577-1965-3
  • Type

    conf

  • DOI
    10.1109/SCET.2012.6341987
  • Filename
    6341987