Share Email Print
cover

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
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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. Imaging. 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)


© SPIE. Terms of Use
Back to Top