Automatic vasculature detection from color fundus images of retina has a significant role in automated diagnosis. Retinal vasculature identification has received importance off late, as it is an important anatomical structure in the analysis of retinopathy. Retinal vasulature can be obtained using any of the basic edge detection techniques but the challenge faced here is in identification of minituare blood vessels . In this paper the applicability of linear prediction residual algorithm for vasculature detection has been analysed. In this case the pixels which fail the prediction are considered as the vasculature edges and are then extracted from the fundus image. The results obtained show that minute blood vessels have also been identified using the proposed approach.
V. Gayathri and Dr. Hema Menon P., “Vasculature detection from retinal color fundus images using linear prediction residual algorithm”, International Journal of Pure and Applied Mathematics, vol. 114, no. 12 Special Issue, pp. 171-178, 2017.