Diabetic　retinopathy　(DR)　is　a　disease　facilitated　by　the　rapid　spread　of　diabetes　worldwide.　DR　can　blind　diabetic　individuals.　Early　detection　of　DR　is　essential　to　restoring　vision　and　providing　timely　treatment.　DR　can　be　detected　manually　by　an　ophthalmologist,　examining　the　retinal　and　fundus　images　to　analyze　the　macula,　morphological　changes　in　blood　vessels,　hemorrhage,　exudates,　and/or　microaneurysms.　This　is　a　time　consuming,　costly,　and　challenging　task.　An　automated　system　can　easily　perform　this　function　by　using　artificial　intelligence,　especially　in　screening　for　early　DR.　Recently,　much　state-of-the-art　research　relevant　to　the　identification　of　DR　has　been　reported.　This　article　describes　the　current　methods　of　detecting　non-proliferative　diabetic　retinopathy,　exudates,　hemorrhage,　and　microaneurysms.　In　addition,　the　authors　point　out　future　directions　in　overcoming　current　challenges　in　the　field　of　DR　research.