Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features

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Publikace nespadá pod Lékařskou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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HA Hien Thi HORÁK Aleš

Rok publikování 2022
Druh Článek v odborném periodiku
Časopis / Zdroj Signal Processing: Image Communication
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www https://www.sciencedirect.com/science/article/pii/S0923596521003015
Doi http://dx.doi.org/10.1016/j.image.2021.116601
Klíčová slova OCR; Information extraction; Scanned documents; Document metadata; Invoice metadata extraction; Metadata indexing
Popis While storing invoice content as metadata to avoid paper document processing may be the future trend, almost all of daily issued invoices are still printed on paper or generated in digital formats such as PDFs. In this paper, we introduce the OCRMiner system for information extraction from scanned document images which is based on text analysis techniques in combination with layout features to extract indexing metadata of (semi-)structured documents. The system is designed to process the document in a similar way a human reader uses, i.e. to employ different layout and text attributes in a coordinated decision. The system consists of a set of interconnected modules that start with (possibly erroneous) character-based output from a standard OCR system and allow to apply different techniques and to expand the extracted knowledge at each step. Using an open source OCR, the system is able to recover the invoice data in 90% for English and in 88% for the Czech set.
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