• DocumentCode
    2323929
  • Title

    An Improved Algorithm for Multiple Closed Contour Detection

  • Author

    Zhang, Tiejun ; Bai, Xufeng ; Song, Xianhua ; Niu, Xiamu

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
  • fYear
    2011
  • fDate
    14-16 Oct. 2011
  • Firstpage
    202
  • Lastpage
    205
  • Abstract
    We present an improved algorithm for the multiple closed contour detection in the multi-object scene, especially for the contours partly occluded by some others. Our method formulates the boundary fragments detected by edge detector from nature image as a graph represented by a reversal symmetry matrix, which incorporates the Gestalt principles of proximity and good continuity as the transition probability between vertices. The algorithm extracts the multiple closed contours by detecting salient cycles in the graph in a global way. It succeeds in extracting the multiple salient closed contours via several iterations even though the occlusion exists. The experiment results show that our algorithm can match or exceed the former ones when extracting isolate smooth closed contour, and do better when facing boundary occlusion cases.
  • Keywords
    edge detection; graph theory; object detection; Gestalt proximity principles; boundary occlusion; edge detector; graph; isolate smooth closed contour; multiobject scene; multiple closed contour detection; nature image; reversal symmetry matrix; salient cycle detection; transition probability; Algorithm design and analysis; Computer vision; Image edge detection; Image segmentation; Pattern analysis; Shape; Signal processing algorithms; Gestalt principle; occluded object; salient contour;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2011 Seventh International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4577-1397-2
  • Type

    conf

  • DOI
    10.1109/IIHMSP.2011.82
  • Filename
    6079502