An Approach to Extract Optic-Disc from Retinal Image Using K-Means Clustering

Abstract

Generally, retinal picture valuation is commonly executed to appraise the diseases. In this paper, an image examination technique is implemented to extract the Retinal-Optic-Disc (ROD) to assess its condition. An approach based on the combination of Kapur's entropy and K-means clustering is considered here to mine the optic disc region from the RGB retinal picture. During the experimental implementation, this approach is tested with the DRIVE and RIM-ONE databases. Initially, the DRIVE pictures are considered to appraise the proposed approach and later, the RIM-ONE dataset is considered for the testing. After extracting the ROD, comparative analyses with the expert's Ground-Truths are carried out and the image similarity values are then recorded. This approach is then validated against the Otsu's+levelset existing in the literature. All these experiments are implemented using Matlab2010. The outcome of this procedure confirms that, proposed work provides better picture similarity values compared to Otsu's+levelset. Hence, in future, this procedure can be considered to evaluate the clinical retinal images.