Possibilistic clustering of generic shapes derived from templates

Tsaipei Wang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present in this paper a new type of alternating-optimization based possibilistic c-shell algorithm for clustering template-based shapes. A cluster prototype consists of a copy of the template after translation, scaling, rotation, and/or affine transformations. We use a number of two-dimensional data sets, both synthetic and from real-world images, to illustrate the capability of our algorithm in detecting generic template-based shapes in images. We also describe a progressive clustering procedure aimed to relax the requirements of known number of clusters and good initialization.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
Pages1721-1728
Number of pages8
DOIs
StatePublished - 7 Nov 2008
Event2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, China
Duration: 1 Jun 20086 Jun 2008

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
CountryChina
CityHong Kong
Period1/06/086/06/08

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