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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 and Aleš HORÁK. Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features. \textit{Signal Processing: Image Communication}. Elsevier, 2022, vol.~102, No~1, p.~1-11. ISSN~0923-5965. Available from: https://dx.doi.org/10.1016/j.image.2021.116601.
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