A Graph Reduction Method for 2D Snake Problems

Energy-minimizing active contour models (snakes) have been proposed for solving many computer vision problems such as object segmentation, surface reconstruction, and object tracking. Dynamic programming which allows natural enforcement of constraints is an effective method for computing the global minima of energy functions. However, this method is only limited to snake problems with one dimensional (1D) topology (i.e., a contour) and cannot handle problems with two-dimensional (2D) topology. In this paper, we have extended the dynamic programming method to address the snake problems with 2D topology using a novel graph reduction algorithm. Given a 2D snake with first order energy terms, a set of reduction operations are defined and used to simplify the graph of the 2D snake into one single vertex while retaining the minimal energy of the snake. The proposed algorithm has a polynomial-time complexity bound and the optimality of the solution for a reducible 2D snake is guaranteed. How...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Jianhua Yan, Keqi Zhang, Chengcui Zhang, Shu-Ching Chen, Giri Narasimhan
• Keywords: 2d Snakes, Computer Vision, CVPR 2007, Reducible 2D Snake, Snake Problems