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Analysis and Detection of Diabetic Retinopathy using Features Extraction Techniques

Published on April 2015 by Manoj M. Mhaske, Ramesh R. Manza, Yogesh M. Rajput, B. P. Gaikwad
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National conference on Digital Image and Signal Processing
Foundation of Computer Science USA
DISP2015 - Number 1
April 2015
Authors: Manoj M. Mhaske, Ramesh R. Manza, Yogesh M. Rajput, B. P. Gaikwad
a964c6b9-8db7-4ce5-be29-888854bcfd04

Manoj M. Mhaske, Ramesh R. Manza, Yogesh M. Rajput, B. P. Gaikwad . Analysis and Detection of Diabetic Retinopathy using Features Extraction Techniques. National conference on Digital Image and Signal Processing. DISP2015, 1 (April 2015), 28-31.

@article{
author = { Manoj M. Mhaske, Ramesh R. Manza, Yogesh M. Rajput, B. P. Gaikwad },
title = { Analysis and Detection of Diabetic Retinopathy using Features Extraction Techniques },
journal = { National conference on Digital Image and Signal Processing },
issue_date = { April 2015 },
volume = { DISP2015 },
number = { 1 },
month = { April },
year = { 2015 },
issn = 0975-8887,
pages = { 28-31 },
numpages = 4,
url = { /proceedings/disp2015/number1/20480-3010/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National conference on Digital Image and Signal Processing
%A Manoj M. Mhaske
%A Ramesh R. Manza
%A Yogesh M. Rajput
%A B. P. Gaikwad
%T Analysis and Detection of Diabetic Retinopathy using Features Extraction Techniques
%J National conference on Digital Image and Signal Processing
%@ 0975-8887
%V DISP2015
%N 1
%P 28-31
%D 2015
%I International Journal of Computer Applications
Abstract

Diabetic Retinopathy is a damage of eye caused by changes in the blood vessels of the retina. Diabetic retinopathy is one of the major problems that lead to blindness in adults around the world today. Early detection of the disease is absolutely essential in preventing unnecessary blindness. So in this paper firstly, we performed preprocessing operations on fundus Images to enhance the images, such as gray scale conversion, Median filter and lastly adaptive histogram equalization. To perform the above functions we have used database from MESSIDOR, this proposed method achieves the rate of specificity and sensitivity. So, we have proposed an automated system to detect diabetic retinopathy from retinal images and classify normal images and abnormal images as Hemorrhages and Exudates. In this approach after pre-processing, texture features are extracted from retinal images and used K-means cluster to classify and detect normal and abnormal images.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Fundus Images