Glaucoma detection using wavelet based contourlet transform

Abstract

One of the leading retinal diseases which cause vision loss is Glaucoma. This paper presents the methodology to detect Glaucoma using wavelet based contourlet transform with Gabor filters. The input retinal fundus image is localized for its region of interest and enhanced using adaptive Gamma correction with weighted Distribution function (AGCWD). The blood vessels in ROI are removed using the Gabor filter and morphological operators. To the Region of Interest the wavelet based contourlet transform (WBCT) is applied to extract the features and then given to the Naïve Bayes (NB) classifiers for detecting the normal and glaucomatous image.