Early Detection of Glaucoma through Retinal Nerve Fiber Layer Analysis Using Fractal Dimension and Texture Feature

The retinal nerve fiber layer (RNFL) is a vital part of human visual system, which can be directly observed by the fundus camera. This paper describes a method for glaucomatous retina detection based on Texture and Fractal description, followed by classification using support vector machine classifier. The color fundus images are used, in which the region of retinal nerve fibers are analyzed. It is shown that Texture & Fractal dimensions are correlated and linear correlation coefficient values are estimated at 0.35, 0.57, and 0.87 for healthy RNFL, medium loss and severe loss of RNFL respectively. The features are measured at 303 RNFL regions retinal positions in the peri-papillary area from 50 non-glaucomatous and 24 glaucomatous retinal fundus images. The presented method can also be used for glaucoma detection. KeywordsRetinal nerve Fiber layer, Glaucoma, Fractal dimension, texture feature, Box counting method -------------------------------------------------------------------***------------------------------------------------------------------