Identification and Classification of Retinal Lesions for Early Detection of Diabetic Retinopathy using Fundal Image

Diabetic Retinopathy (DR) is a human eye disease which may cause damage to retina of eye, it may lead to complete blindness. Currently diabetic retinopathy is detected using different types of lesions such as Microaneursyms (MAs), Exudates (EXs) and Hemorrhages (HAs). This paper focuses on the identification and classification of lesions for early detection of Diabetic retinopathy through hybrid morphological approach. In the proposed approach the detection of DR is performed through hybrid pre-post processing methods to enhance the lesion detection execution. In addition by using the area of boundaries scheme, the affected regions are identified as initial, middle and severe stage. Performance analysis of the proposed method is demonstrated using Matlab software. Simulation studies on available database prove that the hybrid approach has improved performance over classical approach.