Comparison Performance Evaluation of Different Classifiers on Segmented Mammogram Clusters

Abstract

In image processing technique a high resolution images are needed for segmentation and detection and, to interpret the regions in image a high technical tool and skilled personal is needed. Recently many improvements are achieved in this area but still there are some challenges remaining in this direction for better algorithms in detection and segmentation process. The image segmentation method is often used in the processing of medical images. The recent image segmentation procedures incorporate region based segmentation; edge detection segmentation; segmentation depends on clustering. And there also exists number of algorithms to determine the segmented region for detection. This paper deals with a novel technique to compare some special algorithms. The segmented images are undergone for performance evaluation with different algorithms to compare their detection ability. These analysis and summary evaluates and estimates the plus and minus of different algorithms in the image segmentation process. Finally, we can make out the accurate outcome of the development trend in image segmentation with the combination of these algorithms.