Comparison Among Image Clustering Algorithms


Data clustering is a fundamental operation used in unsupervised images generally
clustering involves asset of data (e.g.: image pixels) into specified no of clusters, the
motivation behind clustering is to find inherit structure in the data and to expose the structure
as asset of groups.
Our search concern with taking image clustering problem using four clustering algorithms
named K-mean, K-median, PSO and hybrid of two algorithms, PSO and k-mean. These
algorithms applied on three gray brain images then compare the results.