Standard and Genetic k-means Clustering Techniques in Image Segmentation

Abstract

Clustering or data grouping is a key initial procedure in image processing. This paper deals with the application of standard and genetic k-means clustering algorithms in the area of image segmentation. In order to assess and compare both versions of k-means algorithm and its variants, appropriate procedures and software have been designed and implemented. Experimental results point that genetically optimized k-means algorithms proved their usefulness in the area of image analysis, yielding comparable and even better segmentation results.