Recognition of Unconstrained Legal Amounts Handwritten on Chinese Bank Checks

This paper presents a novel research investigation on legal amount recognition of unconstrained cursive handwritten Chinese character in the environment of A2iA CheckReaderTM ? 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.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Ching Y. Suen, Emmanuel Augustin, Hanshen Tang, Mohamed Cheriet, Olivier Baret
• Keywords: Bank Check Recognition, Computer Vision, ICPR 2004, Real Bank Checks, Recognition Rate