Hard Exudates Detection Method Based on Background-Estimation and SVM Classifier
1 School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China
2 Tianjin Medical University Eye Hospital, Tianjin 300384, China
3 Tianjin Medical University Metabolic Disease Hospital, Tianjin 300070, China
Abstract：Hard exudates (HE) are early symptoms of diabetic retinopathy (DR) and main symptom of macular edema. Hence, HE detection is very important for clinical diagnosis. In this paper, a new method based on backgroundestimation and SVM classifier for hard exudates detection is presented. Firstly, foreground map containing all bright objects is obtained by background-estimation. The HE candidates are gotten using the edge information based on Kirsch operator, and then the optic disc is removed. Finally, the shape features, histogram statistic features and phase features of the HE candidates are extracted before using the SVM classifier so that the accurate extraction of HE is obtained. Our method has been tested on the public databases of DIARETDB1 and HEI-MED. The experiment results show that the method’s sensitivity is 97.3% and the specificity is 90% at the image level, the mean sensitivity is 84.6% and the mean predictive value is 94.4% at the lesion level. The performance of the proposed method shows considerable efficiency for hard exudates detection.
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