Intelligent curve tracking algorithms and implementations
Li Chen, F. T. Berkey, Donald H. Cooley, Yexian He, Jianping Zhang, Lan Zhang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
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.