Glaucoma Detection: An approach using hybrid texture feature descriptors

Abstract

In this paper, we proposed Glaucoma detection in images using a hybrid texture-based Local Binary Pattern (LBP) and Grey Level Co-occurrence Matrix (GLCM) feature descriptors. The significant features are extracted from LBP, GLCM, and LBP+GLCM. Finally, significant features are used with the Support Vector Machine (SVM) classifier for Glaucoma detection. The proposed hybrid texture features descriptors method are used RIM2 dataset for the experimentation and empirical results show that the proposed LBP+GLCM hybrid feature descriptors are efficient than other states of the art techniques.