Open AccessEffective Image Clustering with Differential Evolution Technique
Author(s) -
G Sudhakar,
Preethitha Babu,
Suresh Chandra Satapathy,
Gunanidhi Pradhan
Publication year - 2011
Publication title -
international journal of computer and communication technology
Language(s) - English
Resource type - Journals
eISSN - 2231-0371
pISSN - 0975-7449
DOI - 10.47893/ijcct.2011.1089
Subject(s) - cluster analysis , differential evolution , particle swarm optimization , computer science , image (mathematics) , data mining , artificial intelligence , pattern recognition (psychology) , machine learning
The paper presents a novel approach of clustering image datasets with differential evolution (DE) technique. The differential evolution is a parallel direct search population based optimization method. From our simulations it is found that DE is able to optimize the quality measures of clusters of image datasets. To claim the superiority of DE based clustering we have compared the outcomes of DE with the classical K-means and popular Particle Swarm Optimization (PSO) algorithms for the same datasets. The comparisons results reveal the suitability of DE for image clustering in all image datasets.