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Optimization of manipulation logistics using data matrix codes

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dc.title Optimization of manipulation logistics using data matrix codes en
dc.contributor.author Pivarčiová, Elena
dc.contributor.author Karrach, Ladislav
dc.contributor.author Tučková, Zuzana
dc.relation.ispartof Advances in Science and Technology-Research Journal
dc.identifier.issn 2299-8624 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2018
utb.relation.volume 12
utb.relation.issue 3
dc.citation.spage 173
dc.citation.epage 180
dc.type article
dc.language.iso en
dc.publisher Lublin University of Technology
dc.identifier.doi 10.12913/22998624/94961
dc.relation.uri http://www.astrj.com/OPTIMIZATION-OF-MANIPULATION-LOGISTICS-USING-DATA-MATRIX-CODES,94961,0,2.html
dc.subject Data Matrix en
dc.subject logistics en
dc.subject localization en
dc.subject Finder Pattern en
dc.subject Timing Pattern en
dc.description.abstract In the paper we deal with optimization of manipulation logistics using Data Matrix codes. Our goal is scanning and decoding Data Matrix codes in real-time. We have designed and verified an efficient computer aided method for location of the Data Matrix codes. This method is also suited to real-time processing and has been verified on a test set of images taken from real industrial world. We have proposed a modified, computationally efficient local thresholding technique that uses local mean and variation under the sliding window. The proposed Data Matrix code localization algorithm utilizes the connecting of the adjoining points into the continuous regions and determining of the boundaries of the outer region and it works in two basic steps: localization of the Finder Pattern and verification of the Timing Pattern. Part of the algorithm deals also with the decoding of the Data Matrix code using external libraries. Data Matrix codes can be used to mark logistic units, parts, warehousing positions, but also for automated robot navigation. Because of their low cost, accuracy, speed, reliability, flexibility and efficiency, as well as the ability to write large amounts of data on a small area, they still have a great advantage in logistics. en
utb.faculty Faculty of Logistics and Crisis Management
dc.identifier.uri http://hdl.handle.net/10563/1008421
utb.identifier.obdid 43879224
utb.identifier.wok 000451866500021
utb.source j-wok
dc.date.accessioned 2019-01-31T08:59:01Z
dc.date.available 2019-01-31T08:59:01Z
dc.description.sponsorship [KEGA MS SR 003TU Z-4/2016]
dc.rights Attribution 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Tučková, Zuzana
utb.fulltext.affiliation Elena Pivarčiová 1, Ladislav Karrach 1, Zuzana Tučková 2 1 Technical University in Zvolen, Masarykova 24, 960 53 Zvolen, Slovakia, e-mail: pivarciova@tuzvo.sk, karrach@zoznam.sk 2 Tomas Bata University in Zlín, Department of Logistics, Faculty of Logistics and Crisis Management, Studentské nám. 1532, 686 01 Uherské Hradiště, Czech Republic, e-mail: tuckova@utb.cz
utb.fulltext.dates Received: 2018.07.02 Accepted: 2018.08.01 Published: 2018.09.01
utb.wos.affiliation [Pivarciova, Elena; Karrach, Ladislav] Tech Univ Zvolen, Masarykova 24, Zvolen 96053, Slovakia; [Tuckova, Zuzana] Tomas Bata Univ Zlin, Fac Logist & Crisis Management, Dept Logist, Studentske Nam 1532, Uherske Hradiste 68601, Czech Republic
utb.fulltext.faculty Faculty of Logistics and Crisis Management
utb.fulltext.ou Department of Logistics
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Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International