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In this paper we present an analysis of image features used to discriminate arteries and veins in digital fundus images. Methods proposed in the literature to analyze the vasculature of the retina and compute diagnostic indicators like the Arteriolar to Venular ratio (AVR), use, in fact, different approaches for this classification task, extracting different color features and exploiting different additional information. We concentrate our analysis on finding optimal features for the vesseldoi:10.1109/cbms.2012.6266336 dblp:conf/cbms/ZamperiniGTC12 fatcat:2wts65cpq5b6zkp4qlhk2q6ola