• DocumentCode
    2608348
  • Title

    An improved Prewitt algorithm for edge detection based on noised image

  • Author

    Yang, Lei ; Zhao, Dewei ; Wu, Xiaoyu ; Li, Hui ; Zhai, Jun

  • Author_Institution
    Digital Media Dept., Commun. Univ. of China, Beijing, China
  • Volume
    3
  • fYear
    2011
  • fDate
    15-17 Oct. 2011
  • Firstpage
    1197
  • Lastpage
    1200
  • Abstract
    In this paper, an improved Prewitt algorithm for edge detection is proposed for the reason that the traditional Prewitt edge detection algorithm is sensitive to the noise. The traditional Prewitt edge detection operator only has two templates with horizontal and vertical directions. While the edge is in a plurality of directions, so operator with eight templates of different directions is put forward and it can detect more edges. In order to improve the capability of resisting noise, this paper put forward three improvements. First of all, the mean value rather than the maximum value of the gradient magnitude of the eight directions is used as the final gradient magnitude. Secondly, OTSU automatic threshold is used to set the gradient magnitude threshold. Again, an 8-neighborhood template is proposed to remove the isolated single pixel noise. The experimental results show that the improved algorithm improves the anti noise performance greatly, and detects the edges of the random noised image effectively.
  • Keywords
    edge detection; image denoising; OTSU automatic threshold; Prewitt edge detection algorithm; Prewitt edge detection operator; final gradient magnitude; gradient magnitude threshold; isolated single pixel noise removal; maximum value; random noised image; Algorithm design and analysis; Educational institutions; Image edge detection; Media; Noise; Noise reduction; Signal processing algorithms; OTSU automatic threshold; Prewitt; edge detection; eight-neighborhood denoising;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2011 4th International Congress on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-9304-3
  • Type

    conf

  • DOI
    10.1109/CISP.2011.6100495
  • Filename
    6100495