Curvilinear feature extraction and approximations

Minsoo Suk, Sanghoon Sull

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Most of edge extraction techniques are local operators, thus providing only local information without providing any structural information. Therefore edge points themselves are not adequate as primitive descriptors in computer vision, and local edge points need to be linked into long, straight or slowly curving, line segments. In this paper, a simple and efficient curvilinear feature extraction algorithm using minimum spanning trees is described. The new algorithm is based on the minimum spanning trees found from the edge points. The purpose of finding minimum spanning trees is to link edge points, thus filling gaps and providing structural information. An approximation technique which transforms curvilinear features into straight lines is also described.

Original languageEnglish
Pages (from-to)118-124
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 1983 Oct 26
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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