A new adaptive thresholding technique for retinal vessel segmentation based on local homogeneity information

Abstract

Segmentation of vessels in retinal images has become challenging due to the presence of non-homogeneous illumination across retinal images. This paper develops a novel adaptive thresholding technique based on local homogeneity information for Retinal vessel segmentation. Different types of local homogeneity information were investigated. An experimental evaluation on DRIVE database demonstrates the high performance of all types of homogeneity considered. An average accuracy of 0.9469 and average sensitivity of 0.7477 were achieved. While compared with widely previously used techniques on DRIVE database, the proposed adaptive thresholding technique is superior, with a higher average sensitivity and average accuracy rates in the same range of very good specificity. © 2014 Springer International Publishing.