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CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters

Belur, Dasarathy V and Kumar, Bharath KP (1978) CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters. In: International Journal of Computer & Information Sciences, 7 (3). pp. 253-282.

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Abstract

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 ldquogoodrdquo 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.

Item Type: Journal Article
Additional Information: Copyright of this article belongs to Springer.
Keywords: Character recognition -handprinted alphanumerics - decision tree logic -multistage interleaved feature extraction-categorization approach.
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 21 Sep 2010 07:18
Last Modified: 21 Sep 2010 07:18
URI: http://eprints.iisc.ernet.in/id/eprint/32224

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