Binary pattern recognition using Markov random fields and HMMs
نویسندگان
چکیده
In this paper we present a stochastic framework for the recognition of binary random patterns which advantageously combine hmms and Markov random elds (mrfs). The hmm component of the model analyzes the image along one direction, in a speci c state observation probability given by the product of causal mrf-like pixel conditional probabilities. Aspects concerning de nition, training and recognition via this type of model are developed throughout the paper. Experiments were performed on handwritten digits and words in a small lexicon. For the latter, we report a 89.68% average word recognition rate on the srtp French postal cheque database (7057 words, 1779 scriptors).
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