Template-based online character recognition. (English) Zbl 0970.68756

Summary: 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.


68U99 Computing methodologies and applications
68T10 Pattern recognition, speech recognition


Full Text: DOI


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