2-D shape classification using hidden Markov model
He, Y.
Kundu, A.
Dept. of Electr. & Comput. Eng., State Univ. of New York at Buffalo, Amherst, NY;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Nov 1991
Volume: 13,
Issue: 11
On page(s): 1172-1184
ISSN: 0162-8828
References Cited: 24
CODEN: ITPIDJ
INSPEC Accession Number: 4093257
Digital Object Identifier: 10.1109/34.103276
Current Version Published: 2002-08-06
Abstract
The 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
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