Image segmentation based on solving the flow in the mesh with the connections of limited capacities

Abstract

This paper presents a novel seeded segmentation technique inspired by the flowing of a liquid in a mesh of pipes. The method can be likened to the anisotropic diffusion algorithm. On the other hand, some substantial changes in the relation of how the diffusion works are included. The method is based on the spreading of liquid from the foreground seeds to the neighboring image points that represent basins with an initial amount of liquid. The background seeds drain the liquid from the neighboring basins. If a basin is full or empty, the corresponding pixel becomes a new source or sink. The algorithm runs until all pixels become either sources or sinks. The properties of the method are illustrated on the image segmentation of synthetic images. The comparison with other segmentation techniques is presented on real-life images. The experiments show promising results of the new method.