A skeletonization algorithm by maxima tracking on Euclidean distance transform

Frank Y. Shih, Christopher C. Pu

Research output: Contribution to journalArticlepeer-review

78 Scopus citations


A simple and efficient algorithm using the maxima tracking approach on Euclidean distance transform to detect skeleton points is presented. The advantages of the skeleton obtained are: (1) connectivity preservation; (2) single-pixel in width; and (3) its locations as close as to the most symmetrical axes. Besides, the condition of the least slope change of skeleton is used to ensure the fairness of the digital medial axes. With the least effort, the algorithm can be modified to eliminate non-significant short skeletal branches originating from the object contour while the critical shape-informative medial axes are preserved.

Original languageEnglish (US)
Pages (from-to)331-341
Number of pages11
JournalPattern Recognition
Issue number3
StatePublished - Mar 1995

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


  • Distance transform
  • Image representation
  • Mathematical morphology
  • Medial axis transformation
  • Pattern recognition
  • Skeleton


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