A Efficient Multiple Detection and Classification of Glaucoma Using Mat Lab

Abstract

Glaucoma is one of the 2 nd leading eye diseases in the world, if not treated properly might lead to permanent blindness. There are no specific symptoms for this disease, it is observed by loss of side vision.Glaucoma is a slow progressive degeneration of retinal ganglion cells (RGC) and their axons, resulting in a distinct appearance to the optic nerve head (ONH), often called cupping. Due to cupping, the cup area increases and causes loss of side vision.Usually specially trained clinicians manually grade the fundus images in a time-consuming manner. In this context, we are trying to develop some novel algorithms for automatic detection of eyes affected with glaucoma using image processing filtering & transformation techniques. 5 different concepts are going to be used in our project work for the automatic detection of glaucoma disease in human beings using the concept of fuzzy, artificial neural networks (ANN), neuro-fuzzy (ANFIS), genetic algorithms & using the wavelet features.