Improved Line Operator for Retinal Blood Vessel Segmentation

Abstract

Diabetic retinopathy (DR) is a condition which affects the eye caused by the rise of glucose in the blood. It is the primary cause of sight loss. Blood vessel is among the retinal objects which is altered by DR. By monitoring the the changes of the retinal blood vessel, severe DR or even vision loss can be avoided. Monitoring the condition of the blood vessel can be performed only by segmenting the blood vessel area from a digital fundus image. However, manual segmentation of retinal blood vessel is tedious and time-consuming, especially when processing a large number of images. Thus, automatic retinal blood vessel segmentation method is urgently required. Additionally, automatic retinal blood vessel segmentation methods are also helpful for retina-based person authentication systems. There exist various blood vessel segmentation methods. This study proposes an improved version of the line operator method based on the previous line method [1]. The proposed method is evaluated on the DRIVE dataset and shows improvement in terms of accuracy over previous methods, resulting in 96.24 % accuracy.