Automated segmentation of optic disc in fundus images

This paper presents a method for automated optic disc segmentation from color fundus images. The proposed method comprises three major stages, namely optic disc localization, preprocessing and segmentation. Localization is performed using the fast Fourier transform based template matching to obtain a seed point located on the optic disc which is then used as an input to the region growing technique for the purpose of segmentation. DRIVE database is used to measure the accuracy of the proposed method. From the experimental results, it is found that the proposed localization method achieves success rates of 100%. The proposed segmentation method is compared with several known segmentation methods using the same databse. Based on the results, it is found that the proposed method achieves values of 87.16%, 91.27%, 99.81%, 90.56%, 98.68%, and 89.71% in terms of overlap, sensitivity, specificity, PPV, accuracy, and kappa coefficient respectively, which are higher compared to the results achieved by other known methods.