Detection of Glaucoma Using Retinal Fundus Images with Gabor Filter

Abstract

Glaucoma is an eye disease which causes optic nerve damage. It is a primary cause of permanent blindness.
It is a disease in which the intraocular pressure (IOP) becomes high. A liquid called “aqueous” is continuously flowing
inside the eye. This liquid creates pressure on the internal surface of the eye. If this pressure increases to a great extent,
the possibility of Glaucoma is high. Glaucoma mainly affects the optic disc by increasing the cup size. Glaucoma is one
of the major causes which cause blindness but it can be cured if treated at early stages. Glaucoma is classified using Cup
to Disc Ratio (CDR) of retinal fundus images. Hence an automated Glaucoma diagnosis is required to detect the
abnormality so that when early signs are observed corrective treatments can be prescribed and vision loss can be
prevented. Lots of research has been carried out in detecting the Glaucoma disease. In this paper, a new approach for
detection and grading of Glaucoma by following three methods: (1) Gabor filter is used for detection of optic disc and
cup (2) OTSU’s method is used for thresholding (3) Artificial Neural Network (ANN) is used for classification of the
disease.