標題: | A Flexible Possibilistic C-Template Shell Clustering Method with Adjustable Degree of Deformation |
作者: | Wang, Tsaipei 資訊工程學系 Department of Computer Science |
關鍵字: | shell clustering;template-based clustering;possibilistic c-means;deformable templates |
公開日期: | 2016 |
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. |
URI: | http://hdl.handle.net/11536/134565 |
ISBN: | 978-1-5090-0625-0 |
ISSN: | 1544-5615 |
期刊: | 2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) |
起始頁: | 1516 |
結束頁: | 1522 |
Appears in Collections: | Conferences Paper |