Automated Glaucoma Classification Using Advanced Image Decomposition Techniques From Retinal Fundus Images

Abstract

Glaucoma is one of the main reasons for invariant retinal cecity. Several approaches have been developed to screen glaucoma based on fundus photographs. This chapter investigated automated glaucoma classification methods using advanced image decomposition algorithms such as EWT, DWT, EMD, VMD, and FAWT. This study computed significant texture-based descriptors from the high-frequency descriptors followed by the LS-SVM classifier classification. The robustness of the developed CAD system has been tested using the RIM-ONE public database.