Abstract
This paper reports on a compression method for a reference character dictionary used for on-line Chinese handwriting character recognition, which is based on pattern matching between input and reference patterns. First, one reference pattern for each category is generated from the training data. Second, the reference dictionary is optimized by using the Generalized Learning Vector Quantization (GLVQ) algorithm. Third, the reference dictionaries are compressed to approximately one tenth of the original data using Vector Quantization with the K-means clustering algorithm. Then, the compressed reference dictionaries are again optimized by the GLVQ algorithm. Experimental results for Chinese character recognition show that the dictionary can be successfully compressed without decreasing the recognition rate, and the calculation time of distance between strokes can be reduced by a factor of approximately five.
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References
Sato, A., Yamada, K.: Character Recognition using Generalized Learning Vector Quantization. Technical Report of IEICE, PRU95 219, 23–30 (1996)
Sato, A., Yamada, K.: Generalized Learning Vector Quantization. In: Advances in Neural Information Processing Systems, vol. 8. The MIT Press, Cambridge (1996)
Kitadai, A., Nakagawa, M.: A Learning Algorithm for Structural Pattern Representation used in On-Line Handwritten Character Recognition. Technical Report of IEICE PRMU2000-209, 61–68 (2001-2003)
Tsay, M.-K., Shyu, K.-H., Chang, P.-C.: Feature Transformation with Generalized Learning Vector Quantization for Hand-Written Chinese Character Recognition. IEICE trans E82-D(3), 687–692 (1999)
Kohonen, T.: Self-Organization and Associative Memory, 3rd edn. Springer, Heidelberg (1989)
Kohonen, T.: LVQ PAK Version 3.1 -The Learning Vector Quantization Program Package. LVQ Programming Team of the Helsinki University of Technology (1995)
Nakagawa, M.: Non-keyboard Input of Japanese Text – On-Line Recognition of Handwritten Characters as the Most Hopeful Approach. In: IPSJ Trans. Japan, vol. 13(1), pp. 15–34 ( April 1990)
Tappert, C.C., Suen, C.Y., Wakahara, T.: The State of the Art in On-Line Handwriting Recognition. IEEE Trans. Pattern Anal. Machine Intell. 12(8), 787–808 (1990)
Nakagawa, M., Akiyama, K.: A Linear-time Elastic Matching for Stroke Number Free Recognition of On-Line Handwritten Characters. In: Proc. 4th Int. Workshop on Frontiers in Handwriting Recognition, pp. 48–56 (December 1994)
Hsieh, A., Fan, K., Fan, T.: Bipartite Weighted Matching for On-Line Handwritten Chinese Character Recognition. Pattern Recognition 28(2), 143–151 (1995)
Wakahara, T., Suzuki, A., Nakajima, N., Miyahara, S., Odaka, K.: Stroke- Number and Stroke-Order Free On-Line Kanji Character Recognition as One-to-One Stroke Correspondence Problem. IEICE Trans. Inf. & Syst. E79-D(5), 529–534 (1996)
Uchiyama, T., Sonehara, N., Tokunaga, Y.: On-Line Handwritten Character Recognition Based on Non-Euclidean Distance. IEICE Trans. Inf. & Syst. J80-D-II(10), 2705–2712 (1997) (in Japanese)
Wakahara, T., Odaka, K.: On-Line Cursive Kanji Character Recognition Using Stroke-Based Affine Transformation. IEEE Trans. Pattern Anal. Machine Intell. 19(12), 1381–1385 (1997)
Shin, J., Ali, M.M., Katayama, Y., Sakoe, H.: Stroke Order Free On-Line Character Recognition Algorithm Using Inter-Stroke Information. IEICE Trans. Inf. & Syst. J82-D-II(3), 382–389 (1999) (in Japanese)
Shin, J., Sakoe, H.: Stroke Correspondence Search Method for Stroke-Order and Stroke-Number Free On-Line Character Recognition — Multilayer Cube Search. IEICE Trans. Inf. & Syst. J82-D-II(2), 230–239 (1999) (in Japanese)
Plamondon, R., Lopresti, D.P., Schomaker, L.R.B., Srihari, R.: On-line handwriting recognition. In: Webster, J.G. (ed.) Wiley Ency clopedia of Electrical & Electronics Engineering, New York, pp. 123–146 (1999)
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Shin, J. (2003). A Study of the Compression Method for a Reference Character Dictionary Used for On-line Character Recognition. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_43
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DOI: https://doi.org/10.1007/978-3-540-45224-9_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40803-1
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