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AuthorBen Said, Ahmed
AuthorHadjidj, Rachid
AuthorFoufou, Sebti
Available date2023-10-08T08:41:46Z
Publication Date2015
Publication Name2014 4th International Conference on Image Processing Theory, Tools and Applications, IPTA 2014
ResourceScopus
URIhttp://dx.doi.org/10.1109/IPTA.2014.7001937
URIhttp://hdl.handle.net/10576/48319
AbstractThis 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.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectClustering
Gravity theories
Multispectral images
Segmentation
TitleGravitational weighted fuzzy c-means with application on multispectral image segmentation
TypeConference Paper
dc.accessType Abstract Only


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