Human Retina Optic Disc Segmentation using Statistical Region Merging

Optic disc (OD) localization and segmentation are important tasks in automatic eye disease screening. In this thesis we will present a new, fast and simple iterative methodology for semi-automatic localization and segmentation of the optic disc in fundus images. Furthermore, this new method can find the area of optic disc using the statistical region merging algorithm. The proposed method uses Matlab programming languages for evaluation of algorithm. First, OD location candidates are identified using median filter and Otsu method, then apply the statistical region merging for optic disc localization. The performance of the proposed method will compare with various methods in the literature, and the results are found convincing and efficient. The obtained results indicate that this method of the segmentation of OD has good accuracy.