Abstract
Optic disc (OD) is considered as one of the primary features in retinal fundus images. Detection of the OD is important for the identification and severity assessment of various ophthalmic pathologies. OD localization is the first step towards accurate OD segmentation process. In this paper an adaptive region-based image segmentation method is presented for automated localization of the OD. The proposed method is tested on two publically available datasets of MESSIDOR and DRIVE. For these two datasets, the OD was successfully localized in 90 images out of 100 (90% success) and 38 images out of 40 (95 % success), respectively, with computation time of approximately 1.6 seconds per image. Experimental results indicate that the proposed method is successful in fast and robust OD localization and therefore this method can be useful for real-time automated ophthalmic pathology detection systems.
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