Performance Comparison of Clustering Algorithms Based Image Segmentation on Mobile Devices

In general, clustering concept is used for segmentation of images. In literature, it is found that different clustering approaches are proposed for the purpose of image segmentation. This paper presents comparative analysis of clustering algorithms namely, k-Means (KM), Moving k-Means (MKM), and Enhanced Moving k-Means (EMKM) for image segmentation on mobile devices. Experimentations are carried out on natural images with RGB and HSV color spaces which are used in mobile devices. Performance of KM, MKM, EMKM algorithms is evaluated using qualitative and quantitative parameters, particularly, using Mean Square Error. The obtained results show that the EMKM algorithm is the most suitable technique for image segmentation .