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Impulsive Taxation of Diabetic Maculopathy from Tint Retinal Metaphors

by R. Sukanesh, S. Murugeswari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 11
Year of Publication: 2013
Authors: R. Sukanesh, S. Murugeswari
10.5120/14159-1956

R. Sukanesh, S. Murugeswari . Impulsive Taxation of Diabetic Maculopathy from Tint Retinal Metaphors. International Journal of Computer Applications. 82, 11 ( November 2013), 12-16. DOI=10.5120/14159-1956

@article{ 10.5120/14159-1956,
author = { R. Sukanesh, S. Murugeswari },
title = { Impulsive Taxation of Diabetic Maculopathy from Tint Retinal Metaphors },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 11 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number11/14159-1956/ },
doi = { 10.5120/14159-1956 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:57:27.872544+05:30
%A R. Sukanesh
%A S. Murugeswari
%T Impulsive Taxation of Diabetic Maculopathy from Tint Retinal Metaphors
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 11
%P 12-16
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetic Maculopathy (DM) is a foremost cause of blindness. Exudates are one of the crucial signs of diabetic maculopathy which is a main cause of blindness that could be prevented with an early screening process. In this approach, the process and consciousness of digital image processing to diagnose exudates from images of retina is applied. Presence of exudates and Maculopathy is focused from low-contrast digital images of Diabetic patients' with non-dilated pupils is proposed. Image is segmented by using colour K-means Clustering algorithm. Then segmented image along with Optic Disc (OD) is chosen. Next segmented region, features and texture are extracted. The nominated feature vector are then classified into exudates and non-exudates using a Support Vector Machine (SVM) Classifier. Diabetic Maculopathy, which is the severe stage of Diabetic Retinopathy is accomplished using Morphological Operation. This method performs auspicious as it can detect the very small areas of exudates. Enforced mass airing will help to identify the maculopathy at early stage and reduce the risk of unembellished vision loss. Diabetic Maculopathy is sensed with 100% success rate.

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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Maculopathy Fuzzy k-Means Exudates Dilated Retinal Images.

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