Recognition of Handwritten Digits Using Deformable Models
نویسندگان
چکیده
Deformable models are used to recognize handwritten characters which have a great variety of handwriting styles. The overall character shape is modeled by a B-spline and individual pixels are modeled by Gaussian functions. Model parameters associated with the spline and the Gaussian functions, together with their relative strength, are estimated using Bayesian inference. Under such a Bayesian framework, classiication becomes a process of model selection. This approach has been tested using data in a NIST database and the substitution rate (error rate) is about 4%.
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