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Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04)
Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks
Kokubunji, Tokyo, Japan
October 26-October 29
ISBN: 0-7695-2187-8
| ASCII Text | x | ||
| Hanshen Tang, Emmanuel Augustin, Ching Y. Suen, Olivier Baret, Mohamed Cheriet, "Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks," Ninth International Workshop on Frontiers in Handwriting Recognition, pp. 263-268, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004. | |||
| BibTex | x | ||
| @article{ 10.1109/IWFHR.2004.96, author = {Hanshen Tang and Emmanuel Augustin and Ching Y. Suen and Olivier Baret and Mohamed Cheriet}, title = {Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks}, journal ={Ninth International Workshop on Frontiers in Handwriting Recognition}, volume = {0}, year = {2004}, issn = {1550-5235}, pages = {263-268}, doi = {http://doi.ieeecomputersociety.org/10.1109/IWFHR.2004.96}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Ninth International Workshop on Frontiers in Handwriting Recognition TI - Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks SN - 1550-5235 SP263 EP268 A1 - Hanshen Tang, A1 - Emmanuel Augustin, A1 - Ching Y. Suen, A1 - Olivier Baret, A1 - Mohamed Cheriet, PY - 2004 KW - spiral recognition methodology KW - offline handwriting recognition KW - Asian character recognition VL - 0 JA - Ninth International Workshop on Frontiers in Handwriting Recognition ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IWFHR.2004.96
This paper presents the spiral recognition methodology with its application in unconstrained handwritten Chinese legal amount recognition in a practical environment of a CheckReader™. This paper first describes the failed application of neural network - hidden Markov model hybrid recognizer on Chinese bank check legal amount recognition, and explains the reasons for the failure: the neural network - hidden Markov model hybrid recognizer can not handle the complexity in the training for Chinese legal amounts. Then a spiral recognition methodology is presented. This methodology enables the system to increase its recognition power (both the recognition rate and the number of recognized characters) during the training iterations. Some experiments were done to show that the spiral recognition methodology has a high performance in the recognition of unconstrained handwritten Chinese legal amounts. The recognition rate at the character level is 93.5%, and the recognition rate at the legal amount level is 60%.Combined with the recognition of courtesy amount, the overall error rate is less than 1%.
Index Terms:
spiral recognition methodology, offline handwriting recognition, Asian character recognition
Citation:
Hanshen Tang, Emmanuel Augustin, Ching Y. Suen, Olivier Baret, Mohamed Cheriet, "Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks," iwfhr, pp.263-268, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004
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