CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters
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A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of “good” features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.
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- CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters
International Journal of Computer & Information Sciences
Volume 7, Issue 3 , pp 253-282
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers-Plenum Publishers
- Additional Links
- Character recognition
- handprinted alphanumerics
- decision tree logic
- multistage interleaved feature extraction-categorization approach
- Industry Sectors