K.Priyadharshni, DR.J.Mohana

Abstract

Glaucoma disorder causes damage to human’s optic nerve due to the increased pressure in the eye. In this paper, an efficient method for glaucomatous imageclassification is presented using Dual Tree M-band Wavelet Transform (DTMWT), Probabilistic Principal Component Analysis (PPCA) and Random Forest (RF) classifier. At first, DTMWT is applied to represent the fundus image in multi-resolution that contains lower and higher frequency components. The lower frequency components are reduced by PPCA and then classification is made by RF classifier. The device efficiency is reliably, sensitivity and precisely calculated. Results show that a maximum classification accuracy of 91%, sensitivity of 88%, and specificity of 94% are obtainedby PPCA based DTMWT features with RF classifier.

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