Automatic detection of optic disc based on PCA and stochastic watershed

The algorithm proposed in this paper allows to segment the optic disc from a fundus image. The goal is to facilitate the early detection of certain pathologies and to fully automate the process so as to avoid specialist intervention. The method used for the extraction of the optic disc contour is based on a variant of the watershed transformation, the stochastic watershed. A principal component analysis (PCA) and a previous pre-processing, focused on mathematical morphology, are performed in order to prepare the image for segmentation. The purpose of using PCA is to obtain the grey-scale image that better represents the original RGB image. The implemented algorithm has been validated on a public database obtaining promising results.