Optic Disc Localization in Retinal Images Based on Cumulative Sum Fields

This paper describes an automatic method for the optic disc localization in retinal images, which is effective and reliable with multiple datasets. Particularly, the described method reveals very effective dealing with retinal images with large pathological signs. The algorithm begins with a new vessel enhancement method based on a modified corner detector. Subsequently, a weighted version of the vessel enhancement is combined with morphological operators, to detect the four main vessels orientations $\lbrace 0^\circ, 45^\circ, 90^\circ, 135^\circ \rbrace$ . These four image functions have all the necessary information to determine an initial optic disc localization, resulting in two images that are respectively divided along the vertical or horizontal orientations with different division sizes. Each division is averaged creating a 2-D step function, and a cumulative sum of the different sizes step functions is calculated in the vertical and horizontal orientations, resulting in an initial optic disc position. The final optic disc localization is determined by a vessel convergence algorithm using its two most relevant features; high vasculature convergence and high intensity values. The proposed method was evaluated in eight publicly available datasets, including the STARE and DRIVE datasets. The optic disc was localized correctly in $1752$ out of the $1767$ retinal images $(99.15\%)$ with an average computation time of $18.34$ s.