In medical image processing, segmentation is the one of the significant area of clinical diagnosis and image processing phases. In 'retinal fundus' images, optic disc segmentation plays an important role in analyzing several pathologies, including the abnormalities associated to 'eye retina'. Emerging the perfect automated segmentation of glaucoma region is an extremely hard because of many anomalies present in the input image. In this research paper, presents a method for segmentation/extraction of 'Optic Disc (OD) region' from retinal images along with ROI (Region of Interest) is generated automatically by Visual Saliency Thresholding(VST) method. The mathematical morphology is fully utilized in the proposed segmentation technique. The ROI of OD is recognized by optic cup region with threshold value by means of markers, whereas optic disc is extracted from visual regions through saliency parameters. The achieved experimental results are positive. For assessing the proposed segmentation method that has been verified with many images also compared with the other segmentation algorithms such as Otsu thresholding and region growing. The implementation results direct that proposed technique can be achieved the maximum accuracy than other algorithms. DRISHTI-GS1 dataset is utilized to approve the performance of our proposed segmentation system.