Open AccessExploration of Retinopathy Disease using Machine Learning Methodology
Author(s) -
Khasanah,
Sumardiyono,
Phong Thanh Nguyen,
E. Laxmi Lydia,
K. Shankar
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1173.0886s19
Subject(s) - artificial intelligence , thresholding , computer science , segmentation , computer vision , image segmentation , rgb color model , feature extraction , fundus (uterus) , feature (linguistics) , pattern recognition (psychology) , image processing , image (mathematics) , medicine , ophthalmology , linguistics , philosophy
The whole world is affected with the problem of Diabetic Retinopathy. Whenever a patient has diabetes, it starts affects human body sensitive parts. So the situation becomes very dangerous for the person. Here in this research work it is tried to detect Hemorrhages and micro aneurysms in multiple fundus images collected from various research institutes worldwide and available datasets. In initial it is required to separate RGB colors from the image. The green color is used for further processing. Further the grey color image is extracted for getting the texture of the input image. The feature extraction algorithms are used to classification. So that it is possible to predict the current situation of the retinal image. Once the situation is classified the segmentation algorithms are used using adaptive thresholding segmentation