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

J 2022

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

HA, Hien Thi a Aleš HORÁK

Základní údaje

Originální název

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

Autoři

HA, Hien Thi (704 Vietnam, domácí) a Aleš HORÁK (203 Česká republika, domácí)

Vydání

Signal Processing: Image Communication, Elsevier, 2022, 0923-5965

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.500

Kód RIV

RIV/00216224:14330/22:00125095

Organizační jednotka

Fakulta informatiky

DOI

http://dx.doi.org/10.1016/j.image.2021.116601

UT WoS

000788052500011

Klíčová slova anglicky

OCR; Information extraction; Scanned documents; Document metadata; Invoice metadata extraction; Metadata indexing

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 14. 9. 2024 10:15, doc. RNDr. Aleš Horák, Ph.D.

Anotace

V originále

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.

Návaznosti

LM2018101, projekt VaV

Název: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy (Akronym: LINDAT/CLARIAH-CZ)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, LINDAT/CLARIAH-CZ - Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy

MUNI/A/1195/2021, interní kód MU

Název: Aplikovaný výzkum v oblastech vyhledávání, analýz a vizualizací rozsáhlých dat, zpracování přirozeného jazyka a aplikované umělé inteligence

Investor: Masarykova univerzita, Aplikovaný výzkum v oblastech vyhledávání, analýz a vizualizací rozsáhlých dat, zpracování přirozeného jazyka a aplikované umělé inteligence

Citovat

HA, Hien Thi a Aleš HORÁK. Information Extraction from Scanned Invoice Images using Text Analysis and Layout Features. 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.

@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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