Diabetic retinopathy fundus image classification using discrete wavelet transform

Diabetes is an incurable disease which erodes away body slowly, this disease in becoming common and becoming a cause of social distress. The only solution to this problem is early detection of disease and take precautionary measure to keep its effects to minimum. Since it affects various parts of body, the affected organ also includes eye which is very sensitive to any kind of distress. Diabetic Retinopathy effects of diabetes on eye retina, which includes rupturing of retina blood vessels and abnormal growth of blood vessels in retina, which ultimately causes blindness. Diabetic Retinopathy can be identified by examining the retinoscopy images. In this paper, retinoscopy images were processed using wavelet transform. Wavelet coefficients extracted from the images were obtained to identify Diabetic Retinopathy. KNN and SVM were used to classify the retinoscopy images. This papers have shown remarkable improvement as compared to previous studies, with KNN at 98.16 % accuracy and SVM at 97.85 % accuracy.