Fast Optic Disc Segmentation Using Fft-Based Template-Matching And Vertical Bar Region-Growing Techniques

The analysis of retinal features, such as blood vessels, optic disc and fovea, plays an important role in the detection of several diseases. This paper presents a method for automated optic disc segmentation from colour fundus images. The proposed method comprises three major stages, namely optic disc localisation, preprocessing and segmentation. Localisation 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. Three sets of fundus images, namely DRIVE, MESSIDOR and a LOCAL database are used to measure the accuracy of the proposed method. From the experimental results, it is found that the proposed localisation method achieves success rates of 100, 98.91 and 97.56% for these databases, respectively, which are comparable to other known methods. The proposed segmentation method is compared with several known segmentation methods using DRIVE database. 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, positive predictive value, accuracy, and kappa coefficient respectively, which are higher compared to the results achieved by other known methods. Furthermore, the average processing time required for the optic disc localisation is 0.22 s, while the average processing time required for the entire three stages is1.03 s.