Přejít na obsah

Publikace

Detail publikace

Citace

Lukáš Bureš and Petr Neduchal and Luděk Müller : Automatic Information Extraction from Scanned Documents . SPECOM: International Conference on Speech and Computer, Lecture Notes in Computer Science , vol. 12335, p. 87-96, Springer, Cham, 2020.

Abstrakt

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.

Detail publikace

Název: Automatic Information Extraction from Scanned Documents
Autor: Lukáš Bureš ; Petr Neduchal ; Luděk Müller
Název - česky: Automatic Information Extraction from Scanned Documents
Jazyk publikace: anglicky
Datum vydání: 29.9.2020
Rok vydání: 2020
Typ publikace: Stať ve sborníku
Název časopisu / knihy: SPECOM: International Conference on Speech and Computer
Svazek: Lecture Notes in Computer Science
Číslo vydání: 12335
Strana: 87 - 96
DOI: https://doi.org/10.1007/978-3-030-60276-5_9
ISBN: 978-3-030-60276-5
ISSN: 1611-3349
Nakladatel: Springer, Cham
/ 2021-01-16 09:48:36 /

BibTeX

@INPROCEEDINGS{LukasBures_2020_AutomaticInformation,
 author = {Luk\'{a}\v{s} Bure\v{s} and Petr Neduchal and Lud\v{e}k M\"{u}ller},
 title = {Automatic Information Extraction from Scanned Documents},
 year = {2020},
 publisher = {Springer, Cham},
 journal = {SPECOM: International Conference on Speech and Computer},
 volume = {12335},
 pages = {87-96},
 series = {Lecture Notes in Computer Science },
 ISBN = {978-3-030-60276-5},
 ISSN = {1611-3349},
 doi = {https://doi.org/10.1007/978-3-030-60276-5_9},
 url = {http://www.kky.zcu.cz/en/publications/LukasBures_2020_AutomaticInformation},
}