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Text recognition for objects identification in the industry

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dc.contributor.authorTorres, Pedro
dc.date.accessioned2018-10-15T15:00:03Z
dc.date.available2018-10-15T15:00:03Z
dc.date.issued2017
dc.description.abstractIn line with 4th industrial revolution (Industry 4.0), the mechatronics and related areas are fundamental to boost the developments of industry digitalization. However, it should not be forgotten that artificial intelligence (AI) has a great preponderance on the development of autonomous and intelligent systems incorporating the advances in mechatronics systems. It is common in different industries the need to identify and recognize products or objects for different purposes such as counts, quality control, selection of objects, among others. For these reasons, pattern recognition is increasingly being used in systems on the shop floor, usually implemented in computer vision systems with image processing in real time. This work focuses on automatic detection and text recognition in unstructured images for use on shop floor mechatronic systems with vision systems, to identify and recognize patterns in products. Unstructured images are images that does not have a pre-defined image model or is not organized in a predefined manner. Which means that there is no predefined calibration model, the system must identify and learn by itself to recognize the text patterns. The techniques of character recognition, also known as OCR (Optical Character Reader), are not new in the industry, however the use of machine learning algorithms together with the existing techniques of OCR, allow endow the systems of greater intelligence in the patterns recognition. The results achieved throughout the paper, demonstrates that it is possible to identify and recognize text in objects based on unstructured images with a high level of accuracy and that these algorithms can be used in real time applications.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTORRES. Pedro M. B. (2017) - Text recognition for objects identification in the industry. International Journal of Mechatronics and Applied Mechanics. ISSN 2559-6497. Nº 1, p. 81-84pt_PT
dc.identifier.issn2559-6497
dc.identifier.urihttp://hdl.handle.net/10400.11/6236
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relation.publisherversionhttp://ijomam.com/wp-content/uploads/2017/02/81-84_TEXT-RECOGNITION-FOR-OBJECTS-IDENTIFICATION-IN-THE-INDUSTRY.pdfpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/pt_PT
dc.subjectIndustry 4.0pt_PT
dc.subjectMechatronicspt_PT
dc.subjectMachine visionpt_PT
dc.subjectMachine learningpt_PT
dc.subjectText recognitionpt_PT
dc.titleText recognition for objects identification in the industrypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage84pt_PT
oaire.citation.startPage81pt_PT
oaire.citation.titleInternational Journal of Mechatronics and Applied Mechanicspt_PT
oaire.citation.volume1pt_PT
person.familyNameBAPTISTA TORRES
person.givenNamePEDRO MIGUEL
person.identifierK-5331-2015
person.identifier.ciencia-id2711-E707-519C
person.identifier.orcid0000-0003-4835-5022
person.identifier.scopus-author-id56261515100
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication9d9ad49f-3c45-4a99-be21-7f13965c2628
relation.isAuthorOfPublication.latestForDiscovery9d9ad49f-3c45-4a99-be21-7f13965c2628

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