Accurate and Fast Geodesic Distance Calculation Algorithm for Superpixel Segmentation

Abstract—Modeling in an affine space on the basis of a geodesic distance makes it possible to implement important computer vision techniques. Among these applications is superpixel segmentation, in which geodesic distances from the center of specified segments to an arbitrary image point are calculated. Meanwhile, the algorithms proposed so far for calculating such distances in segmentation problems have been heuristic, iterative approaches, which do not guarantee the expected result. In this study, a new fast algorithm for calculating the geodesic distance is proposed, which is proven to be accurate. The image segments obtained using this algorithm are simply connected regions. The algorithm yields simply connected superpixels at the output, in contrast to many other approaches based on the spatial proximity of the geodesic distance and requiring an additional correction. The proposed technique surpasses its analogs in the border recognition efficiency and computational speed.