Articles

Length estimation of digit strings using a neural network with structure-based features

[+] Author Affiliations
Zhongkang Lu, Zheru Chi, Wan-chi Siu

Hong Kong Polytechnic University, Department of Electronic Engineering, Hung Hom, Kowloon, Hong Kong

J. Electron. Imaging. 7(1), 79-85 (Jan 01, 1998). doi:10.1117/1.482629
History: Received Feb. 22, 1997; Revised June 23, 1997; Accepted Aug. 4, 1997
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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. © 1998 SPIE and IS&T.

© 1998 SPIE and IS&T

Citation

Zhongkang Lu ; Zheru Chi and Wan-chi Siu
"Length estimation of digit strings using a neural network with structure-based features", J. Electron. Imaging. 7(1), 79-85 (Jan 01, 1998). ; http://dx.doi.org/10.1117/1.482629


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