Segmentation of Blood Vessels from Fundus Image Using Scaled Grid

Abstract

This paper proposes an automated technique to segment the retinal blood vessels from funduscopic images. An Adaptive Line Structuring Element (ALSE) [12] is used for initial segmentation, but the process introduces large number of noisy objects accompanying the vessel structure. Fortunately, these noisy objects are relatively isolated structures in comparison to the blood vessels. So, a suitably Scaled Grid can be used to delimit the noisy objects from its neighborhood. When an object falls fully inside a block of the grid, it is considered as a noise and is eliminated. But the objects which passes over the boundary of a block are preserved. The scale of the grid is iteratively increased to identify eventually the all isolated objects and are eliminated without any loss of the actual vessel’s structure. To measure the performance, Accuracy, Sensitivity and Specificity are calculated and compared with the recently found algorithms proposed in the literature.