Handwriting recognition with mixtures of Bayesian networks

Details Handwriting recognition with mixtures of Bayesian networks Handwriting recognition with mixtures of Bayesian networks

2006-02-21

2006-02-21

Miriam, Daniel (Department: 2625)

Image analysis

Pattern recognition

On-line recognition of handwritten characters

C382S159000, C382S228000

Reexamination Certificate

active

07003158

ABSTRACT:
The invention performs handwriting recognition using mixtures of Bayesian networks. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. Each HSBN models the world under the hypothesis that the common external hidden variable is in a corresponding one of its states. The MBNs encode the probabilities of observing the sets of visual observations corresponding to a handwritten character. Each of the HSBNs encodes the probabilities of observing the sets of visual observations corresponding to a handwritten character and given a hidden common variable being in a particular state.

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