Open AccessAutomated Detection of Diabetic Retinopathy Using Intuitionistic Fuzzy Digital Convex Envelope Segmentation Algorithm
Author(s) -
M. S. Swaminathan,
P. Amsini,
R. Uma Rani,
D. Amsaveni
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1012/1/012068
Subject(s) - segmentation , preprocessor , artificial intelligence , computer science , envelope (radar) , digital image , fuzzy logic , pattern recognition (psychology) , diabetic retinopathy , image segmentation , image processing , algorithm , computer vision , image (mathematics) , medicine , diabetes mellitus , telecommunications , radar , endocrinology
Diabetic retinopathy is an ailment of the retinal vessels, which progresses about in most of the diabetes mellitus patients with high blood sugar levels. A framework for automated detection of disorders of the retinal vessels is proposed and examined in this article. As intuitionistic fuzzy sets are being defined through membership and nonmembership functions, they play a vital role in digital image processing to detect the disorder part more clearly. Moreover, shape is a crucial one in numerous areas such as object identification, detection, geomorphology and biology characterization. The intuitionistic fuzzy digital convex envelope is used to measure and analyze the shape of the image of the affected part. The various stages concerned in the process are image acquisition, preprocessing and segmenting the disorder region by the new proposed intuitionistic fuzzy digital convex envelope algorithm. Foremost, this automatic segmentation method reduces the manual work errors and time consuming.