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Computer Optics, 2017, Volume 41, Issue 1, Pages 67–78 (Mi co359)  

IMAGE PROCESSING, PATTERN RECOGNITION

Algorithms for handwritten character recognition based on constructing structural models

P. A. Khaustov

Tomsk Polytechnic University, Tomsk, Russia

Abstract: The article is devoted to the development of algorithms for handwritten character recognition based on constructing structural models. These algorithms do not require a large number of reference images for the correct functioning. Also, an approach to a thinning of the binary character representation based on the joint use of Zhang-Suen and Wu-Tsai algorithms has been proposed. The effectiveness of the proposed approach is confirmed by the results of experiments.
The article includes a detailed description of all steps of the algorithm for constructing structural models. Results of the proposed algorithm's verification are provided, as well as their comparison with other character recognition algorithms. Algorithms that can operate under a limited number of reference images were used for the comparison.

Keywords: character recognition, structural components, structural models, computer vision, skeletonization, binarization.

DOI: https://doi.org/10.18287/2412-6179-2017-41-1-67-78

Full text: PDF file (343 kB)
Full text: http://www.computeroptics.smr.ru/.../410108.html
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Received: 03.06.2016
Accepted:22.12.2016

Citation: P. A. Khaustov, “Algorithms for handwritten character recognition based on constructing structural models”, Computer Optics, 41:1 (2017), 67–78

Citation in format AMSBIB
\Bibitem{Kha17}
\by P.~A.~Khaustov
\paper Algorithms for handwritten character recognition based on constructing structural models
\jour Computer Optics
\yr 2017
\vol 41
\issue 1
\pages 67--78
\mathnet{http://mi.mathnet.ru/co359}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-1-67-78}


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