Gravitational weighted fuzzy c-means with application on multispectral image segmentation
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Gravitational weighted fuzzy c-means with application on multispectral image segmentation |
| Type de publication | Conference Paper |
| Year of Publication | 2014 |
| Auteurs | Ben Said A, Hadjidj R, Foufou S |
| Conference Name | 2014 4TH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA) |
| Publisher | IEEE France Sect; Univ Evry Val Essonne; Informat Biol Integrat & Complex Syst Lab; Inst Technologie UnivEvry Val Essonne; GENOPLOLE; Mutual General Natl Educ; Cooperat Bank Staff Natl Educ Res & Culture; European Assoc Signal Proc; IEEE |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-4799-6463-5 |
| Mots-clés | clustering, gravity theories, multispectral images, segmentation |
| Résumé | This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. A specific weight is associated with each data particle depending on its interaction with other particles. This interaction is induced by attraction forces between pairs of particles and the escape velocity from other particles. Classification experiments using two data sets from UCI repository demonstrate the outperformance of the proposed approach over other clustering algorithms. In addition, results demonstrate the effectiveness of the proposed scheme for segmentation of multispectral face images. |