JIP_V3_N2_RP3 Contrast Enhancement Based Brain Tumour MRI Image Segmentation And Detection With Low Power Consumption B. Shoban Babu S. Varadarajan S. Swarnalatha Journal on Image Processing 2349-6827 3 2 18 25 Contrast Enhancement, Emissive Displays, Histogram Equalization (HE), Histogram Modification (HM), Log Based Histogram Modification (LHM), Low-Power Image Processing, Power Constraint Contrast Enhancement (PCCE), Total Dissipation Power, Image Segmentation, Thresholding Approach, Features Medical image processing is the most challenging topic in the research field. Brain tumour is a serious life altering disease condition. Image segmentation plays a significant role in the estimation of suspicious regions from the medical images. In this paper, two algorithms have been proposed; one algorithm for image enhancement and the other algorithm for image segmentation. The MRI image wherein the brain tumour is to be detected, is enhanced using the proposed technique called Power Constrained Contrast Enhancement (PCCE). Thus, the obtained enhanced image is subjected to image segmentation using threshold point method, to detect the brain tumour. The performance of the proposed method is analysed by computing the parameters of the brain tumour like volume, area, Contrast, Emissive display, mean and standard deviation. These parameter values are compared with the earlier methods, and it found that the performance of the proposed technique of brain tumour detection is quite satisfactory over the earlier existing techniques. April - June 2016 Copyright © 2016 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=6026