TY  - JOUR
T1  - Multi Criterial Analysis for Diabetic Retinopathy
AU - Hephzi Punithavathi, I.S. AU - Ganesh Kumar, P. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 22
SP  - 4681
EP  - 4693
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.4681.4693
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.4681.4693
KW  - microaneurysms
KW  -mathematical morphology
KW  -Diabetic retinopathy
KW  -extreme learning machine
KW  -exudates
AB  - In this study, an automated screening system to diagnose the severity of diabetic retinopathy is
recommended. The proposed system consists of 3 stages; the preprocessing being the first one is done to make
it reliable for extracting features. In the second stage, features like area of blood vessels, exudates, micro
aneurysms and texture features are extracted from the retinal images and classification, the last stage is done
using the ELM classifier. The above procedures were implemented and evaluated using images available in
DIARETDB1 and DRIVE database. Our proposed method shows a high accuracy of 95% and overcomes the
slow training speed when compared with other classifiers.
ER  -