Abstract
Multiplex or multicolor fluorescence in situ hybridization (M-FISH) is a recently developed cytogenetic labeling technique which can be used to find out the chromosomal abnormalities for cancer and genetic disorders. To detect the chromosomal abnormalities, an improved adaptive fuzzy c means clustering algorithm (IAFCM) was developed and applied to the segmentation and classification of M-Fish images. IAFCM method gives considerable classification accuracy among the
existing methods such as FCM and AFCM. In this paper another algorithm k- means clustering is introduced, which runs faster than the IAFCM algorithm. Also a filter can be incorporated with this k- means clustering for denoising. Fuzzy CMeans Clustering is a soft version of K-means, where each data point has a fuzzy degree of belonging to each cluster.