1 Introduction

The recognition of machine printed characters has been intensively studied during the past years and significant progress has been made [l]. For example, there exist commercial OCR systems that achieve a correct recognition rate of over 99% today [a]. But depending on the particular application, such a high recognition rate may be still insufficient. In order to further improve recognition accuracy, contextual postprocessing is often very useful. Different contextual postprocessing methods have been proposed in the literature. A recent survey has been given in [3]. For earlier overviews see [4, 51. In the present paper we propose the application of finite state automata and error-correcting parsing to solve a particular postprocessing problem occurring in the context of automatic check reading. The proposed method is not only an aid to recover from OCR errors but also to classify a document, i.e. a check, based on its contents in the presence of OCR errors. The present paper is a shortened version of [6].