The eye is one of the sensitive organs of the body that is affected by various factors. One of these diseases is glaucoma. Glaucoma is one of the most common ophthalmic diseases that affects the optic disc area and changes this area in terms of size, color and texture. For this reason, the detection of the optic disc area in retinal fundus images is one of the most basic steps in the process of automatic diagnosis of ocular diseases, including glaucoma. Due to the importance of eye diseases and their high incidence, the introduction of new methods in the process of automatic detection of optic disc area by analysis of retinal color images can reduce the volume and computational load, and it helps us to improve the process of early diagnosis of eye diseases. For the reasons mentioned, in this paper, a new method based on the graph-based visual saliency model, along with the watershed algorithm and region growing algorithm to detect optic disc area in retinal fundus images have been suggested to help diagnose eye diseases including glaucoma. According to the proposed method, in this paper, we were able to detect the optic disc area with a 99.1% standard success rate in DRIONS database. تفاصيل المقالة