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17th International Conference on Pattern Recognition (ICPR'04) - Volume 2
Recognition of Unconstrained Legal Amounts Handwritten on Chinese Bank Checks
Cambridge UK
August 23-August 26
ISBN: 0-7695-2128-2
Hanshen Tang, Concordia University, Canada
Emmanuel Augustin, Artificial Intelligence and Image Analysis, France
Ching Y. Suen, Concordia University, Canada
Olivier Baret, Artificial Intelligence and Image Analysis, France
Mohamed Cheriet, ?cole de Technologie Sup?rieure, Canada
This paper presents a novel research investigation on legal amount recognition of unconstrained cursive handwritten Chinese character in the environment of A2iA CheckReader™ - a commercial bank check recognition system. The following problems and their solutions are described: character set of Chinese legal amounts, preprocessing (slant detection and correction), segmentation, feature extraction, grammar, automatic annotation of Chinese characters before and during training, and neural network/hidden Markov model training and recognition. The system is trained with 47.8 thousand real bank checks, and validated with 12 thousand real bank checks. The recognition rate at the character level is 93.5%, and the recognition rate at the legal amount level is 60%. This is the first successful commercial product in this domain.
Citation:
Hanshen Tang, Emmanuel Augustin, Ching Y. Suen, Olivier Baret, Mohamed Cheriet, "Recognition of Unconstrained Legal Amounts Handwritten on Chinese Bank Checks," icpr, vol. 2, pp.610-613, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004
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