Template-based online character recognition
Identifieur interne : 001C45 ( Main/Exploration ); précédent : 001C44; suivant : 001C46Template-based online character recognition
Auteurs : Scott D. Connell [États-Unis] ; Anil K. Jain [États-Unis]Source :
- Pattern Recognition [ 0031-3203 ] ; 1999.
Abstract
Handwriting is a common, natural form of communication for humans, and therefore it is useful to utilize this modality as a means of input to machines. One well-known method of classifying individual characters or words is template matching. We demonstrate a template-based system for online character recognition where the number of representative templates is determined automatically. These templates can be viewed as representing different styles of writing a particular character. The templates are then used as a reference for efficient classification using decision trees. Overall, our classifier achieves an 86.9% accuracy on a set of 17,928 alphanumeric characters (36 classes; 10 digits and 26 lowercase letters) with a throughput of over 8 characters per second on a 296 MHz Sun UltraSparc.
Url:
DOI: 10.1016/S0031-3203(99)00197-1
Affiliations:
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One well-known method of classifying individual characters or words is template matching. We demonstrate a template-based system for online character recognition where the number of representative templates is determined automatically. These templates can be viewed as representing different styles of writing a particular character. The templates are then used as a reference for efficient classification using decision trees. 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