DocumentCode
3041758
Title
Complex curve tracing based on a minimum spanning tree model and regularized fuzzy clustering
Author
Lam, B.S.Y. ; Yan, Hong
Author_Institution
Dept. of Comput. Eng. & Inf. Technol., Hong Kong City Univ., Kowloon, China
Volume
3
fYear
2004
fDate
24-27 Oct. 2004
Firstpage
2091
Abstract
The fuzzy curve-tracing (FCT) algorithm can be used to extract a smooth curve from unordered noisy data. However, the model produces good results only if the curve shape is either opened or closed. In this paper, we propose several techniques to generalize the FCT algorithm for tracing complicated curves. We develop a modified clustering algorithm that can produce cluster centers less dependent on the pre-specified number of clusters, which makes the reordering of cluster centers easier. We make use of the Eikonal equation and the Prim´s algorithm to form the initial curve, which may contain sharp corners and intersections. We also introduce a more powerful curve smoothing method. Our generalized FCT algorithm is able to trace a wide range of complicated curves, such as handwritten Chinese characters.
Keywords
fuzzy set theory; pattern clustering; smoothing methods; trees (mathematics); Eikonal equation; Prim algorithm; cluster center; complex curve tracing; fuzzy clustering; fuzzy curve-tracing algorithm; spanning tree model; unordered noisy data; Clustering algorithms; Data engineering; Data mining; Handwriting recognition; Information technology; Mathematical model; Noise shaping; Partitioning algorithms; Shape; Smoothing methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2004. ICIP '04. 2004 International Conference on
ISSN
1522-4880
Print_ISBN
0-7803-8554-3
Type
conf
DOI
10.1109/ICIP.2004.1421497
Filename
1421497
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