A Two-Stage Classifier for Broken and Blurred Digits in Forms
ICPR(1998)
摘要
A classifier for an automatic system that recognizes multi font typewritten digits, often broken and blurred, in forms is presented. The classification, which is based on the utilization of a global feature, is applied in two phases. Firstly, a minimum distance method (1-NN) is applied in a multifont classifier to provide a global classification of the patterns in a form. A problem associated to multifont classifiers is the interference among classes in different fonts. An interesting aspect of this particular application is that it is highly probable that a form includes just one font. Then, in the second phase, a specialized classifier, oriented to one-form, uses the patterns in the form previously classified to validate, or reject and reclassify them, on the basis of the mean distance to the predefined classes. This specialized classifier affords significant improvement in performance. A classification accuracy rate of 99.42% has been achieved.
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关键词
two-stage classifier,different font,blurred digits,specialized classifier,global feature,multi font typewritten digit,global classification,classification accuracy rate,mean distance,automatic system,minimum distance method,multifont classifier,optical character recognition,handwriting recognition,application software,prototypes,computer architecture,interference,feature extraction,image classification
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