Abstract: Skeleton extraction is an important branch of shape representation and has a wide range of applications in the image compression, pattern recognition and shape matching. This paper proposes a skeleton extraction algorithm based on heat method. The algorithm first constructs triangle meshes for the target region, finds the direction of increasing distance by solving the heat conduction equation, and uses the Poisson equation to restore the geodesic distance. Then the endpoints of the skeletons are determined by using the voting method, and the continuous skeleton lines are obtained by the paths backtracking. Finally, the skeletons of loops are detected and extracted by clustering the end points. The algorithm is robust, accurate and simple to implement since it only needs to solve a pair of standard sparse linear systems. In addition, some information in the pre-calculated can be reused, which reduce memory footprint and time consumption. The experimental results show that the algorithm can extract the skeleton of target shape accurately.

Key words: skeleton extraction, heat method, geodesic distance, voting method