Glaucoma is a disease that destroys the optic nerve of the eye. As a result, it causes vision loss or blindness. However, with immediate diagnosis and treatment, eyes can be protected against severe vision loss. Most vision loss cases due to Glaucoma are preventable if the disease is treated in the early stages. Most Glaucoma cases happen without signs and symptoms because peripheral vision can be damaged before an individual's central vision is affected. The existing procedures to detect Glaucoma are time consuming and inconclusive at the clinic. Thus, the detection can benefit from an automated computer vision-based technique of eye images. Nevertheless, the major problem of intraocular pressure (IOP) that leads to Glaucoma goes under detected. This paper proposes an automatic risk detection process of Glaucoma by extracting a portion of the eye sclera and measuring the red area percentage. The database used in this research was acquired from Princess Basma Hospital containing one hundred facial images divided into fifty healthy cases and fifty non-healthy cases that have high pressure in the eye.