Title :
A New Probabilistic Relaxation Scheme
Author_Institution :
Computer Science Center, University of Maryland, College Park, MD 20742.
fDate :
7/1/1980 12:00:00 AM
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.
Keywords :
Computer science; Distributed computing; Handwriting recognition; Image segmentation; Labeling; Probability distribution; Random variables; Text processing; image processing; line enhancement; relaxation; segmentation;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1980.4767035