A flexible possibilistic c-template shell clustering method with adjustable degree of deformation

Tsaipei Wang*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

This paper presents a new method of template based shell clustering that allows more flexible free deformation of the cluster prototypes with respect to the template-defined shapes. This is achieved via a soft division of the template into several template parts, each allowed to have its own set of transform parameters. A fuzzification factor, inspired by the one used in the standard fuzzy c-means algorithm, is used to control the degree of deformation by blending the transform parameters of the template parts. We demonstrate that this approach gives better shape detection and fitting results than the original possibilistic c-template algorithm using synthetic data of several different shapes.

原文English
主出版物標題2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1516-1522
頁數7
ISBN(電子)9781509006250
DOIs
出版狀態Published - 7 11月 2016
事件2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 - Vancouver, Canada
持續時間: 24 7月 201629 7月 2016

出版系列

名字2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

Conference

Conference2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
國家/地區Canada
城市Vancouver
期間24/07/1629/07/16

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