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title2-D Shape classification using hidden markov model
authorsYang he, Amlan Kundu
keywordsAutoregressive model, hidden markov model, nonstationary transition, pattern recognition, segmental K-means algorithm, shape classification, shape occlusion, shape orientation, stationary test
abstractThe authors present a planar shape recognition approach based on the hidden Markov model and autoregressive parameters. This approach segments closed shapes to make classifications at a finer level. The algorithm can tolerate a lot of shape contour perturbation and a moderate amount of occlusion. An orientation scheme is described to make the overall classification insensitive to shape orientation. Excellent recognition results have been reported. A distinct advantage of the approach is that the classifier does not have to be trained again when a new class of shapes is added.
journalIEEE transactions on pattern analysis and machine intelligence
published year1991
(Total records:1429)
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