Medical image analysis can play a substantial role in diagnosis of different medical problems. Glaucoma is an asymptomatic neurological disease. Oculists mostly use fundoscopy or OpticalCoherence-Tomography (O-C-T) to diagnose glaucoma.Fundoscopy can be used to analyse the external stratum of posterior part of the eye whereas, O-C-T imaging technology has the ability to analyse the internal stratums of posterior part of the eye.In this thesis, a Hybrid Computer Aided Diagnosis (H-CAD) system has been proposed that integrates both fundus and O-C-T imaging technologies for reliable diagnosis. Fundus module has a novel combination of hybrid structural and textural features. The system improves the decision making process after analysing a variety of glaucoma conditions. It further consists of two sub modules Hybrid Structural Feature-set (HSF) and Hybrid Texture Feature-set (HTF). HSF module calculates structural changes i.e. Cupto-Disc-Ratio (C-D-R) and classifies a sample using Support-Vector-Machine (S-V-M). HTF module analyses the textural properties of optic nerve head and again using S-V-M, makes a decision. In O-C-T module, C-D-R has been calculated on the base of the inner stratums of the retina. In the Cup Diameter Extraction (C-D-E) method, cup boundary has been marked on the base of Inner-Limiting-Membrane (I-L-M) stratum. The O-C-T module presents a new method to increase the accuracy of I-L-M stratum segmentation. It also introduces a new method to interpolate missing points on the extracted Upper-Surface of I-L-M stratum (?????). In addition, a novel technique to remove outliers from ????? has been applied. In Disc-Diameter-Extraction (D-D-E) process, Retinal-Pigment-Epithelium (R-P-E) stratum termination points have been used to locate disc margin. Earlier to R-P-E stratum segmentation, I-L-M stratum elimination has been done by a new approach to trace and eliminate I-L-M stratum. Finally, precise R-P-E stratum segmentation has been achieved on the base of new Thickness Value approximation technique. Furthermore, a novel standard for cup boundaries identification, on the base of mean value of R-P-E stratum terminations points is offered. A local-dataset of SD-O-C-T and fundus images annotated by four oculists has been used for evaluation of proposed H-CAD system. Each module ofH_CAD system classifies data independently. The final result of H-CAD system is determined based on decision of three diverse modules. The evaluations and results have shown that the final result of H_CAD system is more trustable than its contemporary automated models.