Glaucoma Detection from Retinal Fundus Images Using RNFL Texture Analysis

Peri-Papillary Atrophy (PPA) is a clinical finding related to chorioretinal diminishing and disorder analysis of the Retinal Pigment Epithelium (RPE) in the region encircling the optic disk. Optical Coherence Tomography (OCT) is an integral asset in clinical perform, used to survey retinal harm in a scope of illnesses. It gives ultra-high-resolution cross-sectional pictures of organic tissues utilizing nonobtrusive imaging innovation. Be that as it may, the examination by OCT is still less open in view of the astonishing costs in various ophthalmology centers wherever all through the world. The primary prerequisite for Peri-papillary-decay investigation in glaucoma analysis is early recognition of RNFL deterioration so as to arrange the treatment process as quickly as time permits. Henceforth, a mass screening agenda is by all accounts appropriate for supporting the finding. Fundus imaging is inexpensive and easily accessible rather than OCT imaging. The contemporary medical accomplishment needs to focus on the analysis procedure basis on the fundus image for the fulfillment of the huge demand of screening process for Glaucoma. In our work we are focusing on Peri-Papillary Atrophy Analysis (PPAA) using Retina Nerve Fiber Layer (RNFL) analysis using Fundus image of retina. In RNFL analysis, we need to identify RNFL loss. This RNFL misfortune can be moderately all around demonstrated as a surface change in fundus photos by analyzing the heterogeneous idea of the Peri-Papillary Atrophy area. RBF kernel based SVM classifier using LDA in combination is applied to achieve the motive of this literature. The experimental results reveal the benefits of the classifier worked on fourteen statistical features.