• DocumentCode
    51574
  • Title

    Extracting Major Lines by Recruiting Zero-Threshold Canny Edge Links along Sobel Highlights

  • Author

    Jaewoong Kim ; Sukhan Lee

  • Author_Institution
    Sch. of Inf. & Commun. Eng., Sungkyunkwan Univ., Suwon, South Korea
  • Volume
    22
  • Issue
    10
  • fYear
    2015
  • fDate
    Oct. 2015
  • Firstpage
    1689
  • Lastpage
    1692
  • Abstract
    A method of extracting major lines from a 2D image is presented. The novelty lies in that major lines are recruited from the maximally generated yet well-thinned zero threshold Canny edge links based on the, so called, Sobel highlights as the guide for recruitment. The Sobel highlights introduced here represent the scores accumulated at individual pixels that measure their significance of forming line segments along Sobel edge orientations. The proposed method offers several advantages over conventional ones: it is 1) more powerful to extract cursive lines, in particular, with a larger curvature, 2) more effective to represent a line as a whole with less intermittent discontinuities, and 3) more straightforward to use as it relies on no sensitive edge thresholding. Experimentations verify that the proposed method outperforms LSD, a top performance major line detector currently available, by about 20% in the coverage of ground truth major lines as well as in the coverage per major line: an intermittent discontinuity indicator. The extraction cycle time is about 54 msec using the Intel i7-2600 CPU and 4G RAM under Window 7.
  • Keywords
    edge detection; image representation; image segmentation; 2D image; 4G RAM under Window 7; Intel i7-2600 CPU; Sobel edge orientations; Sobel highlights; intermittent discontinuity indicator; line detector; zero-threshold Canny edge links; Context; Detectors; Hysteresis; Image edge detection; Indexes; Noise measurement; Recruitment; Curved line; line segment detection; major line; sobel highlight; straight line; zero-threshold canny edge;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2015.2400211
  • Filename
    7031358