3-D Shape Reconstru

We present a method for 3-D shape reconstruction of retinal fundus from fluorescein images. Our method extracts the location of vessels’ bifurcation as a reliable feature for estimating the epipolar geometry using a plane-and-parallax approach. The proposed solution robustly estimates the fundamental matrix for nearly planar surfaces, such as the retinal fundus. We propose the use of mutual information criteria for accurate estimation of the disparity maps, where the matched Y-features are used for automatically estimating the bounds of the disparities range space. Our experimental results validate the proposed method on sets of difficult fluorescein image pairs.