Paper
18 September 1998 Intelligent curve tracking algorithms and implementations
Li Chen, Frank Tom Berkey, Donald H. Cooley, Yexian He, Jianping Zhang, Lan Zhang
Author Affiliations +
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Li Chen, Frank Tom Berkey, Donald H. Cooley, Yexian He, Jianping Zhang, and Lan Zhang "Intelligent curve tracking algorithms and implementations", Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); https://doi.org/10.1117/12.323824
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Fuzzy logic

Genetic algorithms

Neural networks

Image processing

Detection and tracking algorithms

Hough transforms

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