*Corresponding author: Shantala Girradi B.V.B. College of Engineering and Technology, Hubbali, Karnataka, India ISSN: 0976-3031 RESEARCH ARTICLE QUALITY ASSESSMENT AND GRADING OF DIABETIC RETINOPATHY Shantala Girradi, Anoop Betigeri and Chaitra Besthar B.V.B. College of Engineering and Technology, Hubbali, Karnataka, India ARTICLE INFO ABSTRACT Article History: Received 5 th , March, 2015 Received in revised form 12 th , March, 2015 Accepted 6 th , April, 2015 Published online 28 th , April, 2015 Diabetes, caused due to lack of insulin in human blood. This affects some parts of human body one such important organ is eye leading to Diabetic Retinopathy. Diabetic Retinopathy, a complication in diabetic patients, causes damage to retina which in later stages may lead to blindness. The disorder can be detected by regular scanning of the retina of diabetic patients. However, Indian Ophthalmologists to Indian population ratio is 1:90000 which is not proportional necessitating to automation of the system. The proposed system, using Image processing techniques, requires retinal fundus image of an eye taken from fundus camera. But sometimes it is difficult for the system to process due to the dark images leading to misinterpretation in the results. Hence system performs the quality assessment of image by dividing Image into blocks, extracting first order histogram features from retinal image, detecting exudates using AND logic and finally grading the Diabetic Retinopathy as mild, moderate or severe. This paper mainly focuses its content on Image Quality assessment and Retinopathy Grading System. System has achieved 90.9% and 90% of sensitivity and specificity in quality assessment of retinal image. Key words: Diabetic Retinopthy(DR), exudates, macula, retina, quality analysis, AND logic, grading of DR. Copyright © Shantala Girradi, Anoop Betigeri, Chaitra Besthar., This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. INTRODUCTION The most challenging disorder in today’s generation is Diabetes. Though Diabetes is preventive, it is seen as almost inevitable for every individual with their lifestyles. Among 80% of patients who have Diabetes for 10 years or more are likely to be suffer from Diabetic retinopathy, a retinal disorder, leading to vision loss. Since the vision of any individual is precious it needs to be cared the most. During early stage of diabetic retinopathy, NPDR, blood vessels are bulged resulting in soft exudates. In later stages, PDR, abnormal blood vessels are formed. These vessels burst and bleed since those are weak. This forms another type of exudates known as hard exudates. In any of these stages the vision of eye will be reduced and even may result to complete vision loss because of these exudates in macula region of retina. Hence conclusion can be drawn that presence of exudates are key in detecting Diabetic Retinopathy and hence grading it. Method followed to detect Diabetic Retinopathy is regular screening of retina using fundus camera. A research shows that regular screening for diabetic retinopathy could reduces the numbers of people at least by 90% in new cases who develop vision-threatening retinopathy. The estimate of the actual number of diabetics in India is around 40 million and is expected to reach 70 million by 2025. During their lifetime, nearly half of the nation’s estimated 16 million people with diabetes will develop some degree of diabetic retinopathy, and as many as 25,000 people go blind annually. However, it is estimated that the ratio of ophthalmologist to population is 1:90000 in India. This ratio seems not to be proportional as DR needs aggressive screening. Thus it necessitates the need of automated system. This paper presents an automated system which aims to achieve two purposes. First, analyze the quality of the images. Second, grade the diabetic retinopathy by detecting the maculae and exudates region and then grade the DR as mild, moderate and severe. LITERATURE SURVEY With respect to the Quality Analysis, Radhe et al [1], the input image accepted is converted to gray and then using the bit plan separation, contrast enhancement and morphological processing are applied to extract the blood vessels. By using the digital wavelet transforms and the energy feature coefficients are used to get the features and then trained to PNN (probabilistic neural network) and Classification is done with the help of segmentation like K-means Clustering method thereby extracting the exudates determining whether the retina is normal or abnormal and then Morphological operations are applied on segmented image for smoothening the exudates part. But the image without the exudates cannot be used to analyze the Image quality. In the paper described by the Ramon Pires [2] et al, In this methodology, a reference image with assured quality is assumed to be known and quantitative measures of quality for any image are extracted by comparisons with the Available Online at http://www.recentscientific.com International Journal of Recent Scientific Research International Journal of Recent Scientific Research Vol. 6, Issue, 4, pp.3259-3264, April, 2015