Optic disc detection in retinal images using algorithms committee with weighted voting

This paper presents a new method for Optic Disc (OD) detection in color retinal images. Processing and analyzing these images constitute a relevant task to help specialists in eye diseases detection. Particularly, finding OD in a retinal fundus image, improves significantly the chances to detect diseases. OD location serves as input to the detection of other retinal anatomical structures such as macula, blood vessels and some anomalies, such as exudates, hemorrhages and drusen. These anomalies will serve to determine the presence of retinal diseases. We have implemented five OD detection methods from state of art and created a committee of algorithms. Unlike other proposals, based on simple majority vote, the output of the proposed committee is established using a weighted voting obtained by each algorithm. For the definition of the weights we use a portion of available image databases and calculate the success rate of each of the five methods. Tests were carried on six public benchmark databases, which constitute a total of 1566 images.