Publication: Fuzzy logic based edge detection to segment digital images
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Date
2022-08-01
Authors
Kamarullatif, Ikhwan Syazwi
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Abstract
Brain tumour is one of the problems faced by healthcare industry these days. Brain tumour is a result of abnormal cell division in the brain. This problem leads to the death of those who are unfortunate to have this disease. To overcome this problem, we detect the tumour within the brain to find out what is the most appropriate or suitable method to remove it. In this project, we used fuzzy logic-based edge detection approach to segment the brain tumours using MRI images. The image undergoes pre processing by gray scaling and gaussian filtering to prepare the image for segmentation. Two edge detection method were used which is the Sobel edge detection and the Prewitt edge detection. This is combined with the fuzzy logic inference system for the segmentation in which fuzzy sets were specified to classify which pixels according to the degree of membership of the pixels in its membership function. Our proposed method overcomes the problem of uncertainty from separating the tumour from the brain. The system is evaluated using the Dice and Jaccard similarity test by
comparing the output image with the ground truth.