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A novel feature extraction technique for the recognition of segmented handwritten characters

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3 Author(s)
Blumenstein, M. ; Sch. of Inf. Technol., Griffith Univ., Australia ; Verma, B. ; Basli, H.

High accuracy character recognition techniques can provide useful information for segmentation-based handwritten word recognition systems. This research describes neural network-based techniques for segmented character recognition that may be applied to the segmentation and recognition components of an off-line handwritten word recognition system. Two neural architectures along with two different feature extraction techniques were investigated. A novel technique for character feature extraction is discussed and compared with others in the literature. Recognition results above 80% are reported using characters automatically segmented from the CEDAR benchmark database as well as standard CEDAR alphanumerics.

Published in:

Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on

Date of Conference:

3-6 Aug. 2003

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