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In this paper, we present a complete courtesy amount recognition system for Chinese bank checks. The system takes color bank check images as input and consists of three main processing steps: numeral string extraction, segmentation & recognition, and post-processing. They focus sequentially on: detection and extraction of numeral string; segmentation and recognition of the string; and further analysis of recognition results for acceptance or rejection. Information fusion, method complementarity, multi-hypotheses generation then evaluation are three principles employed for designing algorithms in the first two modules. And logistic regression is used for post-processing. A large number of real checks collected from different banks are used for testing the system. Read rate around 82% is observed when the substitution rate is set to 1%, which corresponds to that of a human operator. The performance can also be tuned further toward a suitable balance between inaccuracy and rejection, in accordance with user preference.