  Blindness in diabetic patients caused by retinopathy (characterized by an
increase in the diameter and new branches of the blood vessels inside the
retina) is a grave concern. Many efforts have been made for the early detection
of the disease using various image processing techniques on retinal images.
However, most of the methods are plagued with the false detection of the blood
vessel pixels. Given that, here, we propose a modified matched filter with the
first derivative of Gaussian. The method uses the top-hat transform and
contrast limited histogram equalization. Further, we segment the modified
multiscale matched filter response by using a binary threshold obtained from
the first derivative of Gaussian. The method was assessed on a publicly
available database (DRIVE database). As anticipated, the proposed method
provides a higher accuracy compared to the literature. Moreover, a lesser false
detection from the existing matched filters and its variants have been
observed.
