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Journal of Electronic Imaging

Length estimation of digit strings using a neural network with structure based features
Author(s): Zhongkang Lu; Zheru Chi; Wan-Chi Siu
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Paper Abstract

Accurate length estimation is very helpful for the successful segmentation and recognition of connected digit strings, in particular, for an off-line recognition system. However, little work has been done in this area due to the difficulties involved. A length estimation approach is presented as a part of our automatic off-line digit recognition system. The kernel of our approach is a neural network estimator with a set of structure-based features as the inputs. The system outputs are a set of fuzzy membership grades reflecting the degrees of an input digit string of having different lengths. Experimental results on National Institute of Standards and Technology (NIST) Special Database 3 and other derived digit strings shows that our approach can achieve an about 99.4% correct estimation if the best two estimations are considered.

Paper Details

Date Published: 1 January 1998
PDF: 7 pages
J. Electron. Imag. 7(1) doi: 10.1117/1.482629
Published in: Journal of Electronic Imaging Volume 7, Issue 1
Show Author Affiliations
Zhongkang Lu, Hong Kong Polytechnic Univ. (Hong Kong)
Zheru Chi, Univ. of Sydney (Hong Kong)
Wan-Chi Siu, Hong Kong Polytechnic Univ. (Hong Kong)

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