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In collaboration with financial institutions and utility companies, we have carried out substantial research on document analysis and handwriting recognition. This paper describes our prototype which can differentiate between cheques and remittance slips, between English and French cheques, and recognize their contents. A new technique of sorting handwritten cheques and financial documents will be described. It is based on the detection of the structural properties printed on such documents. Handwritten numeric amounts are recognized by a multiple-expert system. These systems have been applied to read handwritten cheques and numerous financial documents with a great variety of backgrounds, colours, and designs in real-life environments. Their performance will be presented and analyzed.

Magnetic Ink Character Recognition (MICR) was developed about 10 years ago for the automation of cheque and transfer processing in banks and Postgiro’s. In the U.S.A. the E-13B type fount was developed and in Europe CMC-7; their general characteristic is eight characters per inch printing pitch, special printing equipment and a fairly high degree of print quality control. In continental Europe, MICR has not been applied extensively and there is a strong trend noticeable towards Optical Character Recognition (OCR). The primary reason for this is a ten character per inch printing pitch which allows for the use of regular printers, e.g. high-speed printers. It is felt that OCR can provide a better balance between document preparation and reading costs. The subject recognition system was developed specifically with this reasoning in mind. Details of this development are given below.