Abstract
Glaucoma is an eye disease that occurs when circulation of an eye fluid does not remain normal which in turn increases the intraocular pressure (IOP) in aqueous humour of the human eye. This rise of IOP ultimately damages the optic nerve of an eye and leads to complete or partial vision loss. Several image processing techniques have been developed for the detection of glaucoma on the basis of features such as an optic disc (OD), cup to disc ratio (CDR), retinal nerve fibre layer (RNFL) loss, per papillary atrophy (PPA) and neuroretinal rim loss. This paper presents a review of latest work on the use of the model and non-model approaches to detect glaucoma using OD and CDR as glaucoma features.