Extracting Features from the fundus image using Canny edge detection method for PreDetection of Diabetic Retinopathy


EOI: 10.11242/viva-tech.01.04.001

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Citation

Ms. Nishant Dandekar, Ms. Jayesh Kulkarni, Ms. Riddhi Raut, Karishma Raut, "Extracting Features from the fundus image using Canny edge detection method for PreDetection of Diabetic Retinopathy ", VIVA-IJRI Volume 1, Issue 4, Article 52, pp. 1-6, 2021. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Diabetic Retinopathy (DR) is an ailment of the eye caused by diabetes. People suffering from diabetes can procure the disease. DR is caused when the high blood sugar level damages the blood vessels of the eye. Also due to high blood sugar level abnormal blood vessels can grow in the retina. This can make the patient lose its vision. Unfortunately, the symptoms of DR cannot be detected easily. The disease can grow increasingly if left untreated. Hence it becomes all the more important to detect DR. In this paper we have made use of Image processing Technique like canny edge detection to extract the features necessary to detect DR and find the severity of the disease. The features extracted from the image can be used to detect DR by various other methods like SVM, Logistic Regression, etc.

Keywords

Diabetic Retinopathy, Feature Extraction, Canny Edge Detection, Image Processing Technique

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