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Comparative Study of Data Matrix Codes Localization and Recognition Methods

We provide a comprehensive and in-depth overview of the various approaches applicable to the recognition of Data Matrix codes in arbitrary images. All presented methods use the typical “L” shaped Finder Pattern to locate the Data Matrix code in the image. Well-known image processing techniques such...

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Detalles Bibliográficos
Autores principales: Karrach, Ladislav, Pivarčiová, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8471265/
https://www.ncbi.nlm.nih.gov/pubmed/34460799
http://dx.doi.org/10.3390/jimaging7090163
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author Karrach, Ladislav
Pivarčiová, Elena
author_facet Karrach, Ladislav
Pivarčiová, Elena
author_sort Karrach, Ladislav
collection PubMed
description We provide a comprehensive and in-depth overview of the various approaches applicable to the recognition of Data Matrix codes in arbitrary images. All presented methods use the typical “L” shaped Finder Pattern to locate the Data Matrix code in the image. Well-known image processing techniques such as edge detection, adaptive thresholding, or connected component labeling are used to identify the Finder Pattern. The recognition rate of the compared methods was tested on a set of images with Data Matrix codes, which is published together with the article. The experimental results show that methods based on adaptive thresholding achieved a better recognition rate than methods based on edge detection.
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spelling pubmed-84712652021-10-28 Comparative Study of Data Matrix Codes Localization and Recognition Methods Karrach, Ladislav Pivarčiová, Elena J Imaging Article We provide a comprehensive and in-depth overview of the various approaches applicable to the recognition of Data Matrix codes in arbitrary images. All presented methods use the typical “L” shaped Finder Pattern to locate the Data Matrix code in the image. Well-known image processing techniques such as edge detection, adaptive thresholding, or connected component labeling are used to identify the Finder Pattern. The recognition rate of the compared methods was tested on a set of images with Data Matrix codes, which is published together with the article. The experimental results show that methods based on adaptive thresholding achieved a better recognition rate than methods based on edge detection. MDPI 2021-08-27 /pmc/articles/PMC8471265/ /pubmed/34460799 http://dx.doi.org/10.3390/jimaging7090163 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Karrach, Ladislav
Pivarčiová, Elena
Comparative Study of Data Matrix Codes Localization and Recognition Methods
title Comparative Study of Data Matrix Codes Localization and Recognition Methods
title_full Comparative Study of Data Matrix Codes Localization and Recognition Methods
title_fullStr Comparative Study of Data Matrix Codes Localization and Recognition Methods
title_full_unstemmed Comparative Study of Data Matrix Codes Localization and Recognition Methods
title_short Comparative Study of Data Matrix Codes Localization and Recognition Methods
title_sort comparative study of data matrix codes localization and recognition methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8471265/
https://www.ncbi.nlm.nih.gov/pubmed/34460799
http://dx.doi.org/10.3390/jimaging7090163
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