Pattern skeletonization using run-length-wise processing for intersection distortion problem

David X. Zhong, Hong Yan

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Existing skeletonization methods are largely pixel-wise methods which present problems at line pattern intersection regions. Challenged by the problems, we have developed a run-length-wise method in vectorizing line pattern intersections and solving intersection distortion problem in skeletonization. We experimented the method with handwritten Chinese character and numeral character skeletonization to find points of convergence and divergence and to link them into meaningful sets of data. Using these sets of data we construct windows around intersection regions and replace distorted intersection with straight line intersection. Thus we overcome the distortion problem and at the same time retain the smooth property of pixel-wise thinning. © 1999 Elsevier Science B.V.
Original languageEnglish
Pages (from-to)833-846
JournalPattern Recognition Letters
Volume20
Issue number8
DOIs
Publication statusPublished - Aug 1999
Externally publishedYes

Research Keywords

  • Binary image
  • Character recognition
  • Geometric performance
  • Intersection detection
  • Line pattern thinning/skeletonization
  • Run-length processing

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