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Methods of combining multiple classifiers and their applications to handwriting recognition
TLDR
On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly.
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A fast parallel algorithm for thinning digital patterns
A fast parallel thinning algorithm is proposed in this paper. It consists of two subiterations: one aimed at deleting the south-east boundary points and the north-west corner points while the other…
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Thinning Methodologies - A Comprehensive Survey
TLDR
A comprehensive survey of thinning methodologies, including iterative deletion of pixels and nonpixel-based methods, is presented and the relationships among them are explored.
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A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
TLDR
A method was developed which can aggregate the decisions obtained from individual classifiers and derive the best final decisions from the statistical point of view, and outperforms voting, Bayesian, and Dempster-Shafer approaches.
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Application of majority voting to pattern recognition: an analysis of its behavior and performance
  • L. Lam, C. Suen
  • Computer Science
    IEEE Trans. Syst. Man Cybern. Part A
  • 1 September 1997
TLDR
This paper examines the mode of operation of the majority vote method in order to gain a deeper understanding of how and why it works, so that a more solid basis can be provided for its future applications to different data and/or domains.
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The State of the Art in Online Handwriting Recognition
TLDR
The state of the art of online handwriting recognition during a period of renewed activity in the field is described, based on an extensive review of the literature, including journal articles, conference proceedings, and patents.
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Historical review of OCR research and development
TLDR
Both template matching and structure analysis approaches to R&D are considered and it is noted that the two approaches are coming closer and tending to merge.
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Character Recognition Systems: A Guide for Students and Practitioners
TLDR
This chapter discusses the development of Character Recognition, Evolution and Development, and some of the techniques used to achieve this goal, including Bayes Decision Theory, as well as some new methods based onributed graph matching.
A novel hybrid CNN-SVM classifier for recognizing handwritten digits
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Optimal combinations of pattern classifiers
  • L. Lam, C. Suen
  • Computer Science
    Pattern Recognit. Lett.
  • 1 September 1995
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