By Veiga, D.; Pereira, C.; Ferreira, M.; Gon?alves, L.; Monteiro, J.
VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
Digital fundus photographs are often used to provide clinical diagnostic information about several pathologies such as diabetes, glaucoma, macular degeneration and vascular and neurologic disorders. To allow a precise analysis, digital fundus image quality should be assessed to evaluate if minimum requirements are present. Focus is one of the causes of low image quality. This paper describes a method that automatically classifies fundus images as focused or defocused. Various focus measures described in literature were tested and included in a feature vector for the classification step. A neural network classifier was used. HEI-MED and MESSIDOR image sets were utilized in the training and testing phase, respectively. All images were correctly classified by the proposed algorithm.