1 January 1998 Length estimation of digit strings using a neural network with structure based features
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J. of Electronic Imaging, 7(1), (1998). doi:10.1117/1.482629
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.
Zhongkang Lu, Zheru Chi, Wan-Chi Siu, "Length estimation of digit strings using a neural network with structure based features," Journal of Electronic Imaging 7(1), (1 January 1998). http://dx.doi.org/10.1117/1.482629
JOURNAL ARTICLE
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KEYWORDS
Neural networks

Feature extraction

Detection and tracking algorithms

Image segmentation

Databases

Binary data

Fuzzy logic

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