Glaucoma, an eye disease, is often referred to as the silent thief of sight. The damage done by glaucoma is irreversible. There are many types of glaucoma. Early detection and treatment of glaucoma is the only solution. Till date, many works have been done towards automatic glaucoma detection using Fundus Images (FI) by extracting structural features. Structural features can be extracted from optic nerve head (ONH) analysis, cup to disc ratio(CDR) and Inferior, Superior, Nasal, Temporal (ISNT) rule in Fundus Image for glaucoma assessment. But unfortunately, the works till date fall short of expected accuracy in this regard. A review of automated glaucoma detection techniques is presented in this paper.