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@article{1810641, author = {Ha, Hien Thi and Horák, Aleš}, article_number = {1}, doi = {http://dx.doi.org/10.1016/j.image.2021.116601}, keywords = {OCR; Information extraction; Scanned documents; Document metadata; Invoice metadata extraction; Metadata indexing}, language = {eng}, issn = {0923-5965}, journal = {Signal Processing: Image Communication}, title = {Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features}, url = {https://www.sciencedirect.com/science/article/pii/S0923596521003015}, volume = {102}, year = {2022} }
TY - JOUR ID - 1810641 AU - Ha, Hien Thi - Horák, Aleš PY - 2022 TI - Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features JF - Signal Processing: Image Communication VL - 102 IS - 1 SP - 1-11 EP - 1-11 PB - Elsevier SN - 09235965 KW - OCR KW - Information extraction KW - Scanned documents KW - Document metadata KW - Invoice metadata extraction KW - Metadata indexing UR - https://www.sciencedirect.com/science/article/pii/S0923596521003015 N2 - 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. ER -
HA, Hien Thi a Aleš HORÁK. Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features. \textit{Signal Processing: Image Communication}. Elsevier, 2022, roč.~102, č.~1, s.~1-11. ISSN~0923-5965. Dostupné z: https://dx.doi.org/10.1016/j.image.2021.116601.
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