Abstract
The main challenge in handwritten character recognition involves the development of a method that can generate descriptions of the handwritten objects in a short period of time. Due to its low computational requirement, fuzzy logic is probably the most efficient method available for on-line character recognition. The most tedious task associated with using fuzzy logic for online character recognition is the building of the rule-base that would describe the characters to be recognized. The problem is complicated as different people write the same character in complete different ways. This work describes a method that can be used to generate a fuzzy value database that describes the characters written by different individuals.
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Bandara, G., Ranawana, R., Pathirana, S. Use of Fuzzy Feature Descriptions to Recognize Handwritten Alphanumeric Characters. In: K. Halgamuge, S., Wang, L. (eds) Classification and Clustering for Knowledge Discovery. Studies in Computational Intelligence, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11011620_14
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DOI: https://doi.org/10.1007/11011620_14
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26073-8
Online ISBN: 978-3-540-32404-1
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