2021 International Conference on Electronic Engineering (ICEEM)
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Anomaly Detection System for Retinal Images Based on Area Classifier
Oral Presentation , Page 221-224 (4) XML
Volume Title: 2nd IEEE International Conference on Electronic Eng., Faculty of Electronic Eng., Menouf, Egypt, 3-4 July. 2021
Authors
1Dept. of Electronics and Electrical Comm., Faculty of Electronic Engineering, Menouf , Menoufia University, Egypt
2Electronics and Electrical Communication Dept,Faculty of Electronic Engineering,Menoufia University
3Department of Communication and Computer Engineering, Higher Institute of Engineering (HIE), El-Shorouk City, Egypt
4Department of Electronics and Electrical Communications Engineering Faculty of Engineering, Minia University, Egypt
5Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University
6Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University: Menouf, Egypt
7Dept. of Electronics and Electrical Communication, Faculty of Engineering, Minia University, Egypt
8Department of Industrial electronics and control engineering Engineering Faculty of Electronic Engineering Menoufia University: Menouf, Egypt
Abstract
Abstract— Diabetic Retinopathy (DR) is a disease of the eye for diabetics, and it can lead to a lack of vision if leaved untreated. The proposed approach in this paper is used to help for detecting and classifying the DR. It is applied to detect non-proliferative DR by identifying micro-aneurysms and hemorrhages. Firstly, the pre-processing step is applied. It consists of extracting the green channel, removing the optic disc (OD) and normalizing the background. Then, h-maxima transformation is performed. After that, threshold segmentation is applied to detect the hemorrhages and micro-aneurysms, accurately. Finally, an area classifier is used for the classification process to discriminate dark spot lesions.
Keywords