Hybrid Approach for Detection of Hard Exudates
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 3
Abstract
Diabetic Retinopathy is a severe and widely spread eye disease which can lead to blindness. Hence, early detection of Diabetic Retinopathy is a must. Hard Exudates are the primary sign of Diabetic Retinopathy. Early treatment of Diabetic Retinopathy is possible if we detect Hard Exudates at the earliest stage. The main concentration of this paper is to discuss techniques for efficient detection of Hard Exudates. The first technique, discusses Hard Exudates detection using mathematical morphology. The second technique, proposes a Hybrid Approach for Detection of Hard Exudates. This approach consists of three stages: preprocessing, clustering and post processing. In preprocessing stage, we resize the image and apply morphological dilation. The clustering stage applies Linde-Buzo-Gray and k-means algorithm to detect Hard Exudates. In post processing stage, we remove all unwanted feature components from the image to get accurate results. We evaluate the performance of the above mentioned techniques using the DIARETDB1 database which provides ground truth. The optimal results will be obtained when the number of clusters chosen is 8 in both of the clustering algorithms.
Authors and Affiliations
Dr. H. B. Kekre , Dr. Tanuja K. Sarode , Ms. Tarannum Parkar
Keywords
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- EP ID EP130582
- DOI 10.14569/IJACSA.2013.040338
- Views 96
- Downloads 0
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