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Proceedings Paper

Intelligent curve tracking algorithms and implementations
Author(s): Li Chen; Frank Tom Berkey; Donald H. Cooley; Yexian He; Jianping Zhang; Lan Zhang
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Paper Abstract

Real time curve tracking is an important topic in radar image processing and can be applied to automated ionogram scaling and remote target tracking. A 2D gray-scale image only contains line segments and curves, and we want to extract them. For straight line tracking, Hough transform can be applied easily. However, to extract an arbitrary curve, Hough transform requires more processing and data storage costs. According to the nature of the problem, this paper try to find each piece of curves and then link some pieces together to form a curve. A systematic method has been studied in this paper. This method includes the fuzzification of images, fuzzy segmentation, sub-curve search, and genetic algorithm linking. The fuzzification and fuzzy segmentation may not be applied if the original image is clear. the genetic algorithms are designed to link sub-curves in this system. In addition, a fuzzy neural network is proposed and implemented for tracking curves in sequential images.

Paper Details

Date Published: 18 September 1998
PDF: 9 pages
Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); doi: 10.1117/12.323824
Show Author Affiliations
Li Chen, Utah State Univ. and Scientific and Practical Computing (United States)
Frank Tom Berkey, Utah State Univ. (United States)
Donald H. Cooley, Utah State Univ. (United States)
Yexian He, Wuhan Univ. (China)
Jianping Zhang, Utah State Univ. (United States)
Lan Zhang, Utah State Univ. (United States)


Published in SPIE Proceedings Vol. 3371:
Automatic Target Recognition VIII
Firooz A. Sadjadi, Editor(s)

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