Automated Detection and Classification of Glaucoma from Eye Fundus Images: A Survey

Abstract—the identification of eye diseases in retinal image is the subject of several researches in the field of medical image processing. this research proposed a computerized aid diagnosis system to help specialists by displaying useful information such as the location of abnormalities in fundus images This paper is a survey of techniques for Automatic detection of retina image now a days it is plying a vital role in screening tool. This procedure helps to detect various kind of risks and diseases of eyes. Identification of Glaucoma using fundus images involves the measurement of the size, shape of the Optic cup and Neuroretinal rim One of the most common diseases which cause blindness is glaucoma. Early detection of this disease is essential to prevent the permanent blindness. Screenings of glaucoma based on digital images of the retina have been performed in the past few years. Several techniques are there to detect the anomaly of retina due to glaucoma. The key image processing techniques are image registration, image fusion, image segmentation, feature extraction, image enhancement, morphology, pattern matching, image classification, analysis and statistical measurements. The main idea behind this paper is to illustrate a system which is mainly based on image processing and classification techniques for automatic detection of glaucoma by comparing and measuring different parameters of fundus images of glaucoma patients and normal patients