(C) Global Journal Of Engineering Science And Researches [71-73] GLOBAL JOURNAL OFENGINEERINGSCIENCE ANDRESEARCHES AN IMPROVED CLASSIFIER FOR IMAGE SEGMENTATION QUALITY THROUGH EFFECTIVE REGIONMERGING-A SURVEY

In recent years,complexity in finding a particular technique that will give accrate segmentation results for all type of images is growing.In this survey,we have compared different approaches for improving image segmentation quality which are in practice.We have extended our work with fuzzy classifier for improving image segmentation quality through effective region merging.Our method is to start from an over segmented image,which is obtained by applying a standard morphological watershed transformation on the original image.We have efficiently applied the proposed approach to brightness segmentation on different standard test images, with good visual and objective segmentation quality results.The experimental results show that the proposed algorithm is more noise than the standard fuzzy, with more certainity and less fuzziness.This will lead to its practicable and effective applications in medical image segmentation.There is no single method which can be considered good for all type of images,nor all methods equally good for a particular type of image.The proposed method will suit for the accurate segmentation of sequential images