Issue No. 11 - November (1991 vol. 13)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.103276
<p>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.</p>
pattern recognition; segmentation; 2-D shape classification; hidden Markov model; planar shape recognition; autoregressive parameters; shape contour perturbation; occlusion; orientation scheme; shape orientation; Markov processes; pattern recognition
Y. He and A. Kundu, "2-D Shape Classification Using Hidden Markov Model," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 13, no. , pp. 1172-1184, 1991.