This paper deals with the task of information extraction from a structured document scanned by an ordinary office scanner device. It explores the processing pipeline from scanned paper documents to the extraction of searched information such as names, addresses, dates, and other numerical values. We propose system design decomposed into four consecutive modules: preprocessing, optical character recognition, information extraction with a database, and information extraction without a database. In the preprocessing module, two essential techniques are presented – image quality improvement and image deskewing. Optical Character Recognition solutions and approaches to information extraction are compared using the whole system performance. The best performance of information extraction with the database was obtained by the Locality-sensitive Hashing algorithm.
CITATION STYLE
Bureš, L., Neduchal, P., & Müller, L. (2020). Automatic Information Extraction from Scanned Documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12335 LNAI, pp. 87–96). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60276-5_9
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