Recognition of Diabetic Retinopathy / Farrah Murni Syamirah Mohd Affizan

In this day and age, diabetic eye disease is a significant complication of diabetes mellitus which causing visual impairment and blindness. It is the main cause of loss of vision between individuals of working age and it has become a global concern. However, diabetes cannot be detected during physical treatment. Hence, to recognize the symptoms of the diabetic retinopathy, image processing techniques are applied. Images of the retina will be pre-processed first using the enhancement technique where Green Channel is applied. Next, segmentation of the image occurs using Morphology which is top-hat and bottom-hat. Features of the segmented image are extracted using Gray Level Co-Occurrence (GLCM) technique. These features are used as parameters during classification process. Accuracy result is calculated when Support Vector Machine (SVM) that is used for classification managed to recognize diabetic retinopathy. The accuracy of this system is 83.33% and it is developed using MATLAB software. The findings from this study is believed to be helpful as it may contribute in medical image processing field.