• DocumentCode
    1933601
  • Title

    An efficient and accurate approach of detecting elliptical objects in color images

  • Author

    Liu, Yangxing ; Ikenaga, Takeshi ; Goto, Satoshi

  • Author_Institution
    Graduate Sch. of Inf., Production & Syst., Waseda Univ., Tokyo
  • Volume
    2
  • fYear
    2006
  • fDate
    16-20 2006
  • Abstract
    Elliptical object detection in color images is an important step of many image recognition systems. In this paper, we present a novel approach to accurately detect elliptical objects in color images. The proposed method has an important feature of integrating color image edge detection result with a novel ellipse parameter estimation algorithm efficiently. First, we utilize an elaborate edge detection algorithm to extract image edge and obtain precise gradient direction of each edge pixel. Second we carefully select valid edge pixel pairs and an individual edge pixel to accumulate ellipses from the edge map by estimating five parameters of an arbitrary ellipse. The gradient direction information and geometric analysis are intelligently integrated into our algorithm to reduce computation complexity and avoid detecting false ellipses. Experimental results demonstrate that our algorithm is robust and efficient in locating multiple elliptical objects simultaneously with respect to different size, orientation and color
  • Keywords
    geometry; gradient methods; image colour analysis; image recognition; image resolution; object detection; color images; edge pixel; ellipse parameter estimation algorithm; elliptical objects detection; geometric analysis; gradient direction information; image recognition systems; Algorithm design and analysis; Color; Data mining; Image edge detection; Image recognition; Information analysis; Object detection; Parameter estimation; Pixel; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2006 8th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9736-3
  • Electronic_ISBN
    0-7803-9736-3
  • Type

    conf

  • DOI
    10.1109/ICOSP.2006.345706
  • Filename
    4128998