This paper presents a complete numeral amount recognition module which is integrated in an automatic system aimed at reading all types of French checks. This module is combined with an automatic reading system of literal amounts. This complete working system, called LIREChèques, is developed by MATRA MS&I and is now in advanced test at SERINTEL, a pilot site. Two aspects of the numeral amount recognition system are particularly emphasized: the numeral recognition stage itself and the syntactic analysis stage. The numeral recognition module relies on a combination of two individual classifiers, the first one is based on concavity measurements, the second one on both statistical and structural features. The syntactic analysis, called syntactic/contextual analysis, is combined with contextual information to take into account the segmentation behaviour and the presence of literal entities in the numeral amount. We demonstrate that very good performances can be obtained on digits such as those extracted from numeral amounts since a substitution rate of 0.06% while still preserving a recognition rate of near 87% can be achieved. As for the syntactic/contextual analysis stage, results obtained on a test set (containing checks from more than 40 different banks and 15/ of typed checks, thus being a good representation of the real tests realized on site) show clearly that introduction of contextual information in association with syntactic analysis allows to process much more numeral amounts than a simple syntactic analysis and increases perceptibility of the recognition rate.
We present in this paper an automatic recognition module for the handwritten numeral amounts on multibank French checks. This module is integrated on LIREChZques system, a system developed by MATRA CAP Systi?mes, which uses it in collaboration with the automatic recognition of the literal amounts. Two particular aspects of the numeral amount recognition system are detailed : the numeral recognition stage itself and the syntactic analysis. The numeral recognition module filters, by means of a structural supervisor, the digit results derived from the parallel combination of, on one hand a concavity based recognition and on the other hand a structurallstatistical feature based recognition. The syntactic analysis module combines a pure syntactic analysis with contextual information (so called svntacticlcontextual anaiysis) to take into account the segmmtation behaviour and the presence of literal entities.
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