Abstract:
In this paper, we present our ongoing work on
glaucoma classification using fundus images. The approach makes use of texture analysis based on Binary Robust Independent Elementary
Features (BRIEF). This texture measurement is chosen because it can address the illumination issues of the retinal images
and has a lower degree of computational complexity than most of the existing texture measurement methods currently used in the
literature. Contrary to other approaches, the texture measures are extracted from the whole retina image without targeting any
specific region. The method was tested on a set of 196 images composed of 110 healthy retina images and 86 glaucomatous
images and achieved an area under curve (AUC) of 84%. A comparison performance with other texture measurements is also included, which shows our method to be superior.
