This paper presents a baseline system used to evaluate feature sets for word recognition. The main goal is to determine an optimum feature set to represent the handwritten names for the months of the year in Brazilian Portuguese language. Three kinds of features are evaluated: perceptual, directional and topological. The evaluation shows that taken in isolation, the perceptual feature set produces the best results for the lexicon used. These results can be further improved combining the feature sets. The baseline system developed obtains an average recognition rate of 87%. This can be considered a good result considering that no explicit segmentation is performed.
Feature sets evaluation for handwritten word recognition
2002-01-01
279344 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Feature Sets Evaluation for Handwritten Word Recognition
British Library Conference Proceedings | 2002
|Creation of Classifier Ensembles for Handwritten Word Recognition Using Feature Selection Algorithms
British Library Conference Proceedings | 2002
|British Library Conference Proceedings | 2003
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