Template-Based Handwritten Numeric Character Recognition

Ling Hua Li; Shou Fang Mi; Heng Bo Zhang

doi:10.4028/www.scientific.net/AMR.586.384

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 586Template-Based Handwritten Numeric Character...

Template-Based Handwritten Numeric Character Recognition

Abstract:

This paper describes a stroke-based handwriting analysis method in classifying handwritten Numeric characters by using a template-based approach. Writing strokes are variable from time to time, even when the writing character is same and comes from the same user. Writing strokes include the properties such as the number of the strokes, the shapes and sizes of them and the writing order and the writing speed. We describe here a template-based system using the properties of writing strokes for the recognition of online handwritten numeric characters. Experimental results show that within the 1500 numeric characters taken from 30 writers, the system got 97.84% recognition accuracy which is better than other systems shown by other literatures.

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Periodical:

Advanced Materials Research (Volume 586)

Pages:

384-388

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.586.384

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Online since:

November 2012

Authors:

Ling Hua Li, Shou Fang Mi, Heng Bo Zhang

Keywords:

Handwritten Characters Recognition, Online, Stroke, Template-Based

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References

[1] C. C. Tappert, C. Y. Suen, and T. Wakahara, The State of the Art in Online Handwriting Recognition, IEEE Transactions On Pattern Analysis And Machine Intelligence. 12 (1990) 787-808.

DOI: 10.1109/34.57669

Google Scholar

[2] R. Plamondon and S. N. Srihari, On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey, IEEE. Trans. On. Pattern. Analysis. And. Machine. Intelligence. 22 (2000) 63-84.

DOI: 10.1109/34.824821

Google Scholar

[3] V. Vuori, M. Aksela, J. Laaksonen and E. Oja, Adaptive character recognizer for a hand-held device: Implementation and evaluation setup, In Proc. of the 7th IWFHR, 2000, pp.13-22.

Google Scholar

[4] J. Hu, M.K. Brown, and W. Turin, Invariant Features for HMM Based Handwriting Recognition, Proc. ICIAP '95, Sanremo, Italy, Sept. 1995, 588-593.

DOI: 10.1007/3-540-60298-4_318

Google Scholar

[5] B. Huang, Y. Zhang, and M. -T. Kechadi, Preprocessing techniques for online handwriting recognition, Seventh International Conference on Intelligent Systems Design and Applications, 2007, 793-800.

DOI: 10.1109/isda.2007.31

Google Scholar

[6] Abera Abebaw, Implementation Of Online Handwriting Recognition System For Ethiopic Character Set, Ph.D. dissertation, Addis Ababa University, (2007).

Google Scholar

[7] Scott D. Connell, Online Handwriting Recognition using Multiple Pattern Class Models, Ph.D. Thesis, Michigan State University, (2000).

Google Scholar

[8] Vikas Kumar, Template-based Writer-independent Online Character Recognition System using Elastic Matching, MIT International Journal of Computer Science & Information Technology, 1 (2011) 15-18.

Google Scholar