INNOVATIVE
FEATURE SET
FOR RETINOPATHIC ANALYSIS OF DIABETES AND ITS
DETECTION
Abstract:
A fully
automated approach is presented for the feature selection for the application
in diabetic retinopathy. Diabetic Retinopathy(DR) is a vascular disorder
affecting the retina due to prolonged diabetes. It can lead to sudden vision loss
due to DR.This work is aimed to develop an automated system to analyze the
retinal images for extracting important features of diabetic retinopathy using
the image processing techniques. The color retinal images are segmented
following the pre-processing steps, i,e color normalization and contrast enhancement.
The entire segmented images establish a dataset of regions. To classify these
segmented regions into varying changes in blood vessels and different finding
such as exudates, microaneurysms, a set of features such as color, size, edge strength
and texture are extracted which can be used as part of an automated diabetes
recognition system.
Keywords- Fundus image, Diabetic retinopathy, features extraction.
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