Automatic Localization of the Optic Disc in Retinal Fundus Images Using Multiple Features

Accurate optic disc localization is an essential step for a reliable retinal screening system. Existing methods for the optic disc localization may fail when encountering distractors such as imprecise boundaries, deceptive edge features and inconsistent contrast in retinal images. This paper presents an algorithm (Multi-Scheme method) for localization of the optic disc. The algorithm involves prior domain knowledge such as the optic disc size, cup-to-disc ratio (CDR) and vessel convergence feature to evaluate the confidence level for the candidate region(s) at each thresholding level. Based on the confidence level, the algorithm heuristically decides whether or not to opt for multi-scheme policy for a given image. For optimization, the Computed Response (CR) from variant versions of the same image is calculated in parallel and fits a contour to the optic disc through an iterative process of updating the location of the centre of the contour. The proposed approach has been validated using dataset ONHSD [3] and diaretdb0 [16]; and the results show the robustness and reliability of the proposed method even in the presence of distractors.