چکیده (انگلیسی):

Multimodal retinal imaging is an important facet of the diagnosis and therapy of retinal disorders like
retinopathy, occlusion. Many imaging techniques for multimodal retinal images are developing in the recent
years. These novel developments are subjected to a tradeoff between the computational time and effective
registration. This study aims at developing a new algorithm based on the RANSAC matching and gradient
iterative closest point technique which has proven to have less computational time with the best matched
coordinates irrespective of the nature of the input retinal image. This study uses a new adaptive thresholding
technique to extract the bifurcations from the target image and the control points are selected using the RANSAC
matching algorithm. The registration is achieved by implementing gradient iterative closest point algorithm to
minimize the mean square error between the target control points of the base and the reference images.