No abstract

This paper presents an automated method for the detection of exudates and hemorrhages in retina images. The images used here were obtained by the clinical study called "fluorescein angiography" applied to patients who are suffering diabetic retinopathy. Diabetic retinopathy is a condition caused by diabetes prolonged exposition; the condition impairs the vision and could lead to lose it all. Exudates and hemorrhages are two of the damages presented in diabetic retinopathy. The exudates are rounded or oval yellowish-white coatings with indistinct borders and are located superficially in the retina's nerve fiber layer. On the other hand, hemorrhages occur when an abnormal bleeding is located inside the retina's blood vessels.

Agricultural productivity is an important factor in a country's economic development. Therefore, the diagnosis of plant diseases is a field of research of great importance for the agricultural sector since it allows us to help recommend strategies to prevent the spread of diseases, thus reducing economic losses. Currently, with the rise of computer systems, computer systems have been developed that allow computer assisted diagnosis in different fields of research, including the agricultural sector. Since late blight is one of the main diseases due to its high incidence and severity, this paper proposes a methodology to obtain late blight segmentation in tomato leaf images through image analysis and color analysis using the HSV color model. The proposed methodology was applied to a set of publicly available PlantVillage images, to which late blight segmentation was obtained.