A novel fuzzy c-means approach with bit plane algorithm for classification of medical images

This study plays a vital role in the significance of the analysis of an image in medical image processing field, is gaining thought of many researchers in modern times. The recognition of faults present in the destroyed portion of an image is imperative for based field. In this paper, we focus at developing an approach for better classification of medical images. Our methodology is based on the concept of a novel fuzzy approach with bit plane (FCMBP) algorithm. The bit plane filtering method is used to slice the given image for classification to find out the destroyed region of the given image. The sliced image should be normalized with the old techniques and compared with the fuzzy technique for better classification and cluster of the spoiled portion. Thereby the control points have been extracted that are needed for further reconstruction of images. The performance of fuzzy approach with bit plane technique is evaluated using simulation and it is proved that our approach yields better results when compared to accessible methods.

I. Introduction

Imaging is an essential part in medical centres to visualize spoiled portion that exists in medical images obtained through frame grabbers, camera, etc. Popular edge detection techniques (Sobel detector, Robert Cross detector, Canny edge detector, Zero-based detection) can extract boundaries. But due to abrupt change in brightness levels of image in MRI images, we cannot get the correct and smooth edges. Hence medical images have been segmented using fuzzy set theory [1] deals with clustering of images into several regions.