A Novel Set Level Technique for Image Segmentation Using Fuzzy Clustering and Self Organizing Map Network

Image segmentation plays an important role in computer vision or in image processing such as segmentation in video and tracing object of interest, remote sensing, medical treatment and diagnose, for critical disease analysis. In segmentation process all the traditional methods like FCM and K-means are not performed well results in terms of global consistency error and elapse time. The process of image segmentation method also suffered from noise content in image, noise part of image decrease the performance of image segmentation process. For the improvement of image segmentation technique we use fuzzy based clustering technique with some objective function SOM. The motivation is to segment the image with fuzzy based clustering technique with some objective function SOM can enhance the performance.