Green Channel and Top Hat based Image Enhancement for Diabetic Retinopathy Screening

作     者：N A M Sharif A S M Azhar N H Harun J A Bakar A A Abdullah Y F Chong 

作者机构：Data Science Res Lab School of Computing Universiti Utara Malaysia Kedah Malaysia School of Computing Universiti Utara Malaysia Kedah Malaysia Faculty of Electronic Engineering Technology Universiti Malaysia Perlis (UniMAP) Arau Perlis Malaysia Sports Engineering Research Centre (SERC) Universiti Malaysia Perlis 02600 Arau Perlis Malaysia. 

出 版 物：《Journal of Physics: Conference Series》 

年 卷 期：2021年第1997卷第1期

学科分类：07[理学] 0702[理学-物理学] 

摘      要：Diabetic Retinopathy remains one of the most feared diabetes complications that could lead to blindness. Image processing techniques have been widely used all around the world for early detection of diabetic retinopathy. However, most techniques used do not focus on the low visual quality problems in the fundus image. Low visual quality of fundus image may lead to difficulty in evaluation by ophthalmologist before reading it out to the patients. Hence, Automated Screening for Diabetic Retinopathy was created to focus on image enhancement of the fundus image. In this study, two main algorithms for image processing have been used which are green channel conversion and top-hat filters. Green channel in fundus image is selected due to better contrast of the features and background compared to the red and blue channel. While Top-hat filter used to details out small features in the fundus image. The evaluation result of the techniques is compared by using Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Entropy calculations to measure quality of the enhanced fundus images. Results of image enhancement techniques implemented has proved that quality of the fundus image is improved.