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Proceedings Paper

Curvilinear Feature Extraction And Approximations
Author(s): Minsoo Suk; Sanghoon Sull
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Paper Abstract

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.

Paper Details

Date Published: 26 October 1983
PDF: 7 pages
Proc. SPIE 0397, Applications of Digital Image Processing V, (26 October 1983); doi: 10.1117/12.935288
Show Author Affiliations
Minsoo Suk, Korea Advanced Institute of Science and Technology (Korea)
Sanghoon Sull, Korea Advanced Institute of Science and Technology (Korea)

Published in SPIE Proceedings Vol. 0397:
Applications of Digital Image Processing V
Andre J. Oosterlinck; Andrew G. Tescher, Editor(s)

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