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2-D shape classification using hidden Markov model

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2 Author(s)
Y. He ; Dept. of Electr. & Comput. Eng., State Univ. of New York at Buffalo, Amherst, NY, USA ; A. Kundu

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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IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:13 ,  Issue: 11 )