Mathematical Problems in Engineering
Volume 2011 (2011), Article ID 416963, 12 pages
Research Article

Improved Generalized Belief Propagation for Vision Processing

1College of Computer Science, Zhejiang University of Technology, Hangzhou 310023, China
2School of Information Science & Technology, East China Normal University, No. 500, Dong-Chuan Road, Shanghai 200241, China
3School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210046, China

Received 29 September 2010; Accepted 25 October 2010

Academic Editor: Cristian Toma

Copyright © 2011 S. Y. Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Generalized belief propagation (GBP) is a region-based belief propagation algorithm which can get good convergence in Markov random fields. However, the computation time is too heavy to use in practical engineering applications. This paper proposes a method to accelerate the efficiency of GBP. A caching technique and chessboard passing strategy are used to speed up algorithm. Then, the direction set method which is used to reduce the complexity of computing clique messages from quadric to cubic. With such a strategy the processing speed can be greatly increased. Besides, it is the first attempt to apply GBP for solving the stereomatching problem. Experiments show that the proposed algorithm can speed up by 15+ times for typical stereo matching problem and infer a more plausible result.