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Proceedings Paper

Principal curve detection in complicated graph images
Author(s): Yuncai Liu; Thomas S. Huang
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Paper Abstract

Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.

Paper Details

Date Published: 20 September 2001
PDF: 6 pages
Proc. SPIE 4552, Image Matching and Analysis, (20 September 2001); doi: 10.1117/12.441549
Show Author Affiliations
Yuncai Liu, Shanghai Jiao Tong Univ. (China)
Thomas S. Huang, Univ. of Illinois/Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 4552:
Image Matching and Analysis
Bir Bhanu; Jun Shen; Tianxu Zhang, Editor(s)

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