Stochastic relaxation on partitions with connected components and its application to image segmentation

Jia-Ping Wang
1998 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We present a new method of segmentation in which images are segmented by partitions with connected components. For this, rst we de ne two di erent types of neighborhoods on the space of partitions with connected components of a general graph; neighborhoods of the rst type are simple but small, while those of the second type are large but complex; second, we give algorithms which are not computationally costly, for probability simulation and simulated annealing on such spaces using the
more » ... ods. In particular Hastings algorithms and generalized Metropolis algorithms are de ned to avoid heavy computations in the case of the second type of neighborhoods. To realize segmentation, we propose a hierarchical approach which at each step minimizes a cost function on the space of partitions with connected components of a graph.
doi:10.1109/34.683775 fatcat:mgaalm55mng5rpqy7yvxmnv46e