Please use this identifier to cite or link to this item:
Title: Length estimation of digit strings using a neural network with structure-based features
Authors: Lu, Z
Chi, ZG 
Siu, WC 
Issue Date: Jan-1998
Source: Journal of electronic imaging, Jan. 1998, v. 7, no. 1, p. 79-85
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.
Keywords: Feature extraction
Feedforward neural nets
Fuzzy neural nets
Image recognition
Image segmentation
Multilayer perceptrons
Parameter estimation
Publisher: SPIE-International Society for Optical Engineering
Journal: Journal of electronic imaging 
ISSN: 1017-9909
EISSN: 1560-229X
DOI: 10.1117/1.482629
Rights: Lu Z, Chi Z and Siu W, "Length estimation of digit strings using a neural network with structure-based features," J. Electron. Imaging., 7(1), p. 79-85 (1998)
Copyright 1998 Society of Photo-Optical Instrumentation Engineers & Society for Imaging Science and Technology. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Lu_Lenath_Estimation_Diait.pdf142.96 kBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Full Text


Last Week
Last month
Citations as of Aug 29, 2020


Last Week
Last month
Citations as of Sep 26, 2020

Page view(s)

Last Week
Last month
Citations as of Sep 29, 2020


Citations as of Sep 29, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.