Color Retinal Image Analysis for Automated Detection and Severity of Exudates

Sarika Madhu, Parameshachari B D,Nithin Joe, H S DivakaraMurthy


Diabetic macular edema (DME) is an advanced symptom of diabetic retinopathy and can lead to irreversible vision loss. In this paper, a two-stage methodology for the detection and classification of DME severity from color fundus images is proposed. DME detection is carried out via a supervised learning approach using the normal fundus images. A feature extraction technique is introduced to capture the global characteristics of the fundus images and discriminate the normal from DME images. Disease severity is assessed using a rotational asymmetry metric by examining the symmetry of macular region.

Keywords - abnormality detection;hard exudate;rotational symmetry;motion generation;severity checking

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