A Hybrid Recogniser for Handwritten Symbols Based on Fuzzy Logic and Self-Organizing Maps

In this paper we present a hybrid approach to handwritten symbol recognition based on two different methods and principles. A fuzzy rules based recogniser and a self-organizing map recogniser are combined to form our hybrid system. These two systems complement each other well, firstly because their...

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Bibliographic Details
Main Authors: Cronin, A., Fitzgerald, J.A., Kechadi, T.
Format: Conference Proceeding
Language:English
Subjects:
Character recognition
Computer science
Educational institutions
Feature extraction
Fuzzy logic
Fuzzy systems
Handwriting recognition
Informatics
Keyboards
Multiple Classifier Systems
Self organizing feature maps
Self-Organizing Maps
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Summary:In this paper we present a hybrid approach to handwritten symbol recognition based on two different methods and principles. A fuzzy rules based recogniser and a self-organizing map recogniser are combined to form our hybrid system. These two systems complement each other well, firstly because their feature extraction techniques differ greatly, and secondly because one is a model-based and the other is a discriminative classifier. Each system generates a ranked list of outputs with associated confidence values, and these outputs are combined to produce a single result. The approach has achieved high recognition rates in testing on digits and lowercase characters from the UNIPEN database
ISSN:1082-3409
2375-0197
DOI:10.1109/ICTAI.2006.13