Abstract
Let a vector of probabilities be associated with every node of a graph. These probabilities define a random variable representing the possible labels of the node. Probabilities at neighboring nodes are used iteratively to update the probabilities at a given node based on statistical relations among node labels. The results are compared with previous work on probabilistic relaxation labeling, and examples are given from the image segmentation domain. References are also given to applications of the new scheme in text processing.
Original language | English |
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Pages | 337-343 |
Number of pages | 7 |
State | Published - 1979 |
Event | Proc IEEE Comput Soc Conf Pattern Recognition Image Process - Chicago, IL, USA Duration: 6 Aug 1979 → 8 Aug 1979 |
Conference
Conference | Proc IEEE Comput Soc Conf Pattern Recognition Image Process |
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City | Chicago, IL, USA |
Period | 6/08/79 → 8/08/79 |