• DocumentCode
    557660
  • Title

    A robust structure extraction method based on image edge

  • Author

    Yang Guang ; Hu Lei ; Lu Qichao ; Gao Feng

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    15-17 Oct. 2011
  • Firstpage
    855
  • Lastpage
    859
  • Abstract
    In this paper, we propose a novel approach with desirable universality and expansibility for structural feature extraction. Structural feature is a high-level 2D feature that delivers information including image components and spatial relations of them. In the proposed approach, we first trace edges to line segments, fit line segments to longer lines and extract parallel pairs. Then, we extract contours of image components by grouping lines and parallel pairs. Lastly, we reveal the salient spatial relations of components by theorems and judging rules. The theorems, which are concluded from the step of components extraction, facilitate the following analytical procedure. Experimental results tested on 1960 real images demonstrate that our approach can extract integrated contours of image components and analyze the spatial relations between them in desirable time consuming, and the approach is suitable for many application fields.
  • Keywords
    edge detection; feature extraction; contours extraction; grouping lines; high-level 2D feature; image components; image edges; line segment edge tracing; salient spatial relation; spatial relation; structural feature extraction method; Complexity theory; Computer vision; Feature extraction; Image edge detection; Image segmentation; Pattern recognition; Target recognition; image edge; structure extraction; structure feature;
  • 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.2011.6100265
  • Filename
    6100265