Author(s): Veiga, Diana ; Pereira, Carla ; Ferreira, Manuel João Oliveira ; Gonçalves, Luís ; Monteiro, João L.
Date: 2014
Persistent ID: https://hdl.handle.net/1822/29492
Origin: RepositóriUM - Universidade do Minho
Subject(s): Digital fundus photography; Focus measures; Image processing
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.
