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JACIII Vol.3 No.6 pp. 462-466
doi: 10.20965/jaciii.1999.p0462
(1999)

Paper:

An Evolutionary Algorithm for Optimizing Handwritten Numeral Templates Represented by Rational B-Spline Surfaces

Zheru Chi*, Zhongkang Lu*, Wan-chi Siu* and Peng-Fei Shi**

*Centre of Digital Signal Processing for Multimedia Applications Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hung Hom, Kowloon, Hong Kong

**Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai, 200030, P. R. of China

Received:
June 23, 1999
Accepted:
August 23, 1999
Published:
December 20, 1999
Keywords:
Handwritten numeral string recognition, Evolutionary algorithms, Template optimization, Template matching
Abstract

To improve the reliability of a template-matching classifier for recognizing connected handwritten characters, we present an evolutionary algorithm to optimize handwritten numeral templates represented by rational Bspline surfaces of character pixel-boundary distance maps (PBDMs). Initial templates are extracted by training a feed-forward neural network. In simulation, 1,000 handwritten numeral templates (100 templates for each class) were extracted and optimized using 10,426 training samples (isolated numerals from NIST Special Database 3). A template-matching classifier using these 1,000 optimized templates rejected 90.7% of nonnumeral patterns (not included in the training set) while achieving a correct classification rate of 96.4% on independent isolated numerals.

Cite this article as:
Zheru Chi, Zhongkang Lu, Wan-chi Siu, and Peng-Fei Shi, “An Evolutionary Algorithm for Optimizing Handwritten Numeral Templates Represented by Rational B-Spline Surfaces,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.6, pp. 462-466, 1999.
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