International Journal of Computer Application Issue 2, Volume 3 (june 2012) Issn: 2250-1797

Segmentation refers to the process of partitioning a digital image into multiple segments known as super-pixels. Image segmentation is typically used to locate objects and boundaries in images. SOM-K, a new unsupervised natural image segmentation method based on SOM and k-means. Intensity and L*, U*, V* values of a color image are taken as features to be trained by a SOM network. The output prototype vectors are filtered by the hit map at first and clustered by the k-means method. The method is proved to be robust to natural color image segmentation through experiments. In this paper we are comparing SOM-Based Fuzzy C-Means Clustering algorithm to taken different types of Remote Sensing data to test the performance. We compare the quality measures standard deviation, variance and also we can detect the images based on various Edge Detection techniques for efficient segmentation. Corresponding Author: