Fuzzy genetic clustering for pixel classification of satellite images

We evaluate the performance of two fuzzy cluster validity indices, including a recently developed index, PBMF. The effectiveness of variable string length genetic algorithm (VGA) is used in conjunction with the fuzzy indices to determine the number of clusters present in a data set as well as the proper fuzzy cluster configuration. The utility of the fuzzy partitioning is tested on a number of artificial and real life data sets. The results of the fuzzy VGA algorithm are compared with those obtained by the well known FCM (fuzzy C-means) algorithm which is applicable only when the number of clusters is known a priori. The performance of the two fuzzy cluster validity indices is also tested for the pixel classification of a remotely sensed image of the race-course ground of Kolkata.