Image Segmentation from Consensus Information

Kyujin Cho and Peter Meer

Department of Electrical and Computer Engineering
Rutgers University, Piscataway, NJ 08855, USA

A new approach toward image segmentation is proposed. A set of slightly different segmentations are derived from the same input and the final result is based on the consensus among them. The perturbations are introduced by exploiting the probabilistic component of a region adjacency graph (RAG) pyramid based segmentation. From the set of initial segmentations the cooccurrence probability field is obtained in which global information about the delineated regions becomes locally available. The final segmentation is based on this field and is obtained with the same hierarchical, RAG pyramid technique. No user set parameters or context dependent thresholds are required.

Appeared in Computer Vision and Image Understanding, vol. 68, 72-89, October 1997.
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