An Application of Genetic Algorithm with Iterative Chromosomes for Image Clustering Problems

Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. This paper represents a Genetic Algorithm for clustering on image data. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. In this study, a heuristic method based on Genetic Algorithms (GA) is adopted to automatically determine the number of cluster centroids during unsupervised classification. Efficient time techniques are used as a performance measure for clustering on image data. This paper compares Genetic algorithm with K-Means algorithm for clustering on image data.