Optic Disc Segmentation Based on Correlation Feature Information

Abstract

Glaucoma, one of the major causes of blindness, has been identified as a disease that causes the degeneration of the optic disc. An highly accurate automated detection of the optic disc (OD) has however been noted to be of great importance for the efficient diagnosis of the disease. This paper presents a study on an unsupervised approach usage of Haralick Correlation texture feature for the segmentation of optic disc in colored fundus retinal images. The grayscale and green channel of the colored fundus image are investigated. When compared with some methods in the literature, the experimental study of the proposed method achieved very high average accuracy rates of 98.59% and 98.36% using grayscale and green channel of the colored fundus image respectively on DRIVE database.