Automatic detection of defects from Diabetic Patient Retinal Fundus Images can help to detect and observe Diabetic Retinopathy which is further leads to Diabetic Retinopathy complications. Mathematically strong system is required to calculate accurately DR features like localization micro aneurysms, hemorrhages, exudate and optic disk in a retinal image is presented in this project. Since these features has different intensity properties, geometric features and correlations are used to distinguish between them. We propose method for optic disk detection, where we first detect the major blood vessels and use the intersection of these to find the approximate location of the optic disk. This is further localized using color properties. We also show that many of the features such as the blood vessels, exudate and micro aneurysms and hemorrhages can be detected quite accurately using different morphological operations applied appropriately. Algorithms are used to effectively calculate and identify features from fundus image database with varied contrast, illumination and disease stages the success in finding the defects in DR affected patient iris fundus image. These compare very favorably with existing systems and promise real deployment of these systems.