Diabetic Retinopathy Early Detection Using Bag of Features Point Dependent Image Processing Methods (International Journal of Innovative Research in Computer Science & Technology, 2021)
Diabetic Retinopathy (DR) is a major  problem that impairs anthropological eyesight. It is usually  formed at the rear side of the eye retina, when light sensitive tissues' blood vessels are damaged. Based on  symptoms or diseases in the eye, such as mild visual  difficulties, vision loss, blindness, damage to blood vessels  in the retina caused by high blood sugar levels, etc.,  attention is required. Investigators have confronted a  crucial test for the early identification of eye illness using  image recognition methods for many years. A method for  automatically identifying diabetic retinopathy based on  topographies such as point-based from retinal pictures  utilizing SVM and basket of topographies techniques.  There are four steps in this procedure: The input eye retina  picture is pre-processed in the first step. We smear re scaling geometric changes like revolution for picture  enhancement in the second phase. In the third stage, we  present an automated technique based on point-based  features and a list of pictures for first diabetes or non diabetic diagnosis utilizing SVM and a basket of  topographies such as Haar modification image processing  methods. Lastly, we liken the measurements like RMSE,  PSNR, Elapsed Time and Accuracy utilizing this future  method.
Keywords: Diabetic Retinopathy (DR); Elapsed Time (ET); Haar Transformation; Peak Signal Noise Ratio (PSNR); Root Mean Square Error (RMSE); Support Vector Machine (SVM)