Convergence condition and efficient implementation of the fuzzy curve-tracing (FCT) algorithm

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
Hong Yan

Abstract

The fuzzy curve-tracing (FCT) algorithm can be used to extract a smooth curve from unordered noisy data. In this paper, we analyze the convergence property of the algorithm based on the diagonal dominance requirement of the matrix used in the clustering procedure and prove that the algorithm is guaranteed to converge if the weighting coefficient for the smoothness constraint is chosen properly. Based on the convergence condition, we develop several methods for fast and reliable implementation of the algorithm. We show that the algorithm can be initialized with a user-defined curve in many cases, that a multiresolution clustering based approach and an image down-sampling scheme can be used to improve the algorithm stability and speed and that two types of traps can be removed to correct the mistakes in curve tracing. We demonstrate several advantages of our algorithm over the commonly used snake models for boundary detection and several methods for principle curve extraction.

References

Sep 17, 2004·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Hong Yan
Feb 16, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·C Xu, J L Prince
Jan 1, 1996·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·A J Abrantes, J S Marques
Jan 1, 1980·IEEE Transactions on Pattern Analysis and Machine Intelligence·J C Bezdek

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Citations

Jan 9, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Pradipta Maji, Sankar K Pal
Sep 1, 2011·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Chung-Chih TsaiChin-Wang Tao
Sep 17, 2004·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Hong Yan
Jul 3, 2015·Computers in Biology and Medicine·Wen-Bo ZhuQing-Lin Chen
Aug 19, 2015·IEEE Transactions on Neural Networks and Learning Systems·Shubhra Sankar RaySankar K Pal

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