IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of degraded characters using dynamic Bayesian networks
Pattern Recognition
Feature space and metric measures for fusing multisensor images
International Journal of Remote Sensing
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A comparison is made between several Hidden Markov Models in the context of printed character recognition. Two HMMs are first compared, one dealing with columns of a character image, the other dealing with lines. These 2 HMMs are then associated in a decision fusion scheme combining the log-likelihoods provided by each HMM classifier. The statistical assumptions underlying the combination formula are described and the combination formula is shown to be an approximation of a real joint log-likelihood. The last experiment consists in building a single HMM, modeling the joint flow of lines and columns. This data fusion scheme is shown to be more accurate as it highlights correlations between line and column features.