6533b7d2fe1ef96bd125df57

RESEARCH PRODUCT

Gravitational weighted fuzzy c-means with application on multispectral image segmentation

Sebti FoufouAhmed Ben SaidRachid Hadjidj

subject

Fuzzy clusteringSegmentation-based object categorizationbusiness.industryCorrelation clusteringScale-space segmentationPattern recognitionSegmentationImage segmentationArtificial intelligenceCluster analysisbusinessFuzzy logicMathematics

description

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.

yearjournalcountryeditionlanguage
2014-10-012014 4th International Conference on Image Processing Theory, Tools and Applications (IPTA)
https://doi.org/10.1109/ipta.2014.7001937