This paper describes an off-line system which recognizes unconstrained handwritten month words extracted from Canadian bank cheques. A segmentation based grapheme level HMM (hidden Markov model) classifier and two multilayer perceptron classifiers with different architectures and different features have been developed in CENPARMI for the recognition of month words. In this paper, a combination method with an effective conditional topology is presented, and the most widely used combination rules including Vote, Sum and Product, are experimented. A new modified Product rule is also proposed, which has produced the best recognition rate of 85.36% when tested on a real-life standard Canadian bank cheque database. Copyright © 2000 IEEE Computer Society.
|Title of host publication||Proceedings of the 8th International Workshop on Frontiers in Handwriting Recognition|
|Place of Publication||Niagara-a-the-Lake, Canada|
|Publisher||IEEE Computer Society|
|Publication status||Published - 2002|
CitationXu, Q., Kim, H. J., Lam, S. W. L. & Suen, C. Y. (2002). Recognition of handwritten mouth words on bank cheques. In Proceedings of the 8th International Workshop on Frontiers in Handwriting Recognition (pp. 111-116). Niagara-a-the-Lake, Canada: IEEE Computer Society.
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