Comparison of manual and automatic barcode detection in rough horticultural production systems
Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success. Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner, and factors su...
Gespeichert in:
| Veröffentlicht in: | International journal of agricultural and biological engineering 2019-11, Vol.12 (6), p.169-176 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 176 |
|---|---|
| container_issue | 6 |
| container_start_page | 169 |
| container_title | International journal of agricultural and biological engineering |
| container_volume | 12 |
| creator | Eyahanyo, Felix Rath, Thomas |
| description | Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success. Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner, and factors such as speed, angle of inclination of the barcode, damage to the barcode and dirt on the barcode. Furthermore, laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming, which leading to reduced productivity. Therefore, an automated image-based barcode detection system to help solve the aforementioned problems was proposed. Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company. The images were analyzed with a specific algorithm developed with the software tool Halcon. Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery. |
| doi_str_mv | 10.25165/j.ijabe.20191206.4762 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2335162402</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2335162402</sourcerecordid><originalsourceid>FETCH-LOGICAL-c230t-7bad1190359cbed58917efdc85d35b2a1098575d1c6bd8ececb96292c269c1f43</originalsourceid><addsrcrecordid>eNo9kMtOwzAQRS0EEqXwC8gS6wQ_YideogooUiU2sMXyKzRRExc_Fv17TAus5i7OzB0dAG4xqgnDnN2P9TAq7WqCsMAE8bppOTkDCyxoU3HKyPl_bppLcBXjiBBvOsoW4GPlp70KQ_Qz9D2c1JzVDqrZQpWTn1QaDNQqGG8dtC45k4ZCDjMMPn9u4daHQuRdyqGs7YO3-UTEQ0xuitfgole76G5-5xK8Pz2-rdbV5vX5ZfWwqQyhKFWtVhZjgSgTRjvLOoFb11vTMUuZJgoj0bGWWWy4tp0zzmjBiSCGcGFw39AluDvdLS98ZReTHH0Oc6mUhNJiiTSIFIqfKBN8jMH1ch-GSYWDxEgeXcpRHl3KP5fyxyX9BqBha18</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2335162402</pqid></control><display><type>article</type><title>Comparison of manual and automatic barcode detection in rough horticultural production systems</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Eyahanyo, Felix ; Rath, Thomas</creator><creatorcontrib>Eyahanyo, Felix ; Rath, Thomas ; 1. Leibniz University of Hannover, Institute of Horticultural Production Systems, Biosystems Engineering Section, Herrenh鋟ser Stra遝 2, 30419 Hannover, Germany ; 2. University of Applied Sciences Osnabr點k, Biosystems Engineering Laboratory (BLab), Oldenburger Landstra遝 24, 49090 Osnabr點k, Germany</creatorcontrib><description>Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success. Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner, and factors such as speed, angle of inclination of the barcode, damage to the barcode and dirt on the barcode. Furthermore, laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming, which leading to reduced productivity. Therefore, an automated image-based barcode detection system to help solve the aforementioned problems was proposed. Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company. The images were analyzed with a specific algorithm developed with the software tool Halcon. Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.</description><identifier>ISSN: 1934-6344</identifier><identifier>EISSN: 1934-6352</identifier><identifier>DOI: 10.25165/j.ijabe.20191206.4762</identifier><language>eng</language><publisher>Beijing: International Journal of Agricultural and Biological Engineering (IJABE)</publisher><subject>Agricultural production ; Algorithms ; Automation ; Bar codes ; Dirt ; Experiments ; Flowers ; Horticulture ; Image detection ; Inclination angle ; Laboratories ; Lasers ; Localization ; Morphology ; Nurseries ; Radio frequency identification ; Scanners ; Software ; Software development tools</subject><ispartof>International journal of agricultural and biological engineering, 2019-11, Vol.12 (6), p.169-176</ispartof><rights>2019. This work is published under https://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Eyahanyo, Felix</creatorcontrib><creatorcontrib>Rath, Thomas</creatorcontrib><creatorcontrib>1. Leibniz University of Hannover, Institute of Horticultural Production Systems, Biosystems Engineering Section, Herrenh鋟ser Stra遝 2, 30419 Hannover, Germany</creatorcontrib><creatorcontrib>2. University of Applied Sciences Osnabr點k, Biosystems Engineering Laboratory (BLab), Oldenburger Landstra遝 24, 49090 Osnabr點k, Germany</creatorcontrib><title>Comparison of manual and automatic barcode detection in rough horticultural production systems</title><title>International journal of agricultural and biological engineering</title><description>Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success. Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner, and factors such as speed, angle of inclination of the barcode, damage to the barcode and dirt on the barcode. Furthermore, laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming, which leading to reduced productivity. Therefore, an automated image-based barcode detection system to help solve the aforementioned problems was proposed. Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company. The images were analyzed with a specific algorithm developed with the software tool Halcon. Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.</description><subject>Agricultural production</subject><subject>Algorithms</subject><subject>Automation</subject><subject>Bar codes</subject><subject>Dirt</subject><subject>Experiments</subject><subject>Flowers</subject><subject>Horticulture</subject><subject>Image detection</subject><subject>Inclination angle</subject><subject>Laboratories</subject><subject>Lasers</subject><subject>Localization</subject><subject>Morphology</subject><subject>Nurseries</subject><subject>Radio frequency identification</subject><subject>Scanners</subject><subject>Software</subject><subject>Software development tools</subject><issn>1934-6344</issn><issn>1934-6352</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNo9kMtOwzAQRS0EEqXwC8gS6wQ_YideogooUiU2sMXyKzRRExc_Fv17TAus5i7OzB0dAG4xqgnDnN2P9TAq7WqCsMAE8bppOTkDCyxoU3HKyPl_bppLcBXjiBBvOsoW4GPlp70KQ_Qz9D2c1JzVDqrZQpWTn1QaDNQqGG8dtC45k4ZCDjMMPn9u4daHQuRdyqGs7YO3-UTEQ0xuitfgole76G5-5xK8Pz2-rdbV5vX5ZfWwqQyhKFWtVhZjgSgTRjvLOoFb11vTMUuZJgoj0bGWWWy4tp0zzmjBiSCGcGFw39AluDvdLS98ZReTHH0Oc6mUhNJiiTSIFIqfKBN8jMH1ch-GSYWDxEgeXcpRHl3KP5fyxyX9BqBha18</recordid><startdate>20191101</startdate><enddate>20191101</enddate><creator>Eyahanyo, Felix</creator><creator>Rath, Thomas</creator><general>International Journal of Agricultural and Biological Engineering (IJABE)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QO</scope><scope>7SN</scope><scope>7ST</scope><scope>7T7</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BVBZV</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>RC3</scope><scope>SOI</scope></search><sort><creationdate>20191101</creationdate><title>Comparison of manual and automatic barcode detection in rough horticultural production systems</title><author>Eyahanyo, Felix ; Rath, Thomas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c230t-7bad1190359cbed58917efdc85d35b2a1098575d1c6bd8ececb96292c269c1f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Agricultural production</topic><topic>Algorithms</topic><topic>Automation</topic><topic>Bar codes</topic><topic>Dirt</topic><topic>Experiments</topic><topic>Flowers</topic><topic>Horticulture</topic><topic>Image detection</topic><topic>Inclination angle</topic><topic>Laboratories</topic><topic>Lasers</topic><topic>Localization</topic><topic>Morphology</topic><topic>Nurseries</topic><topic>Radio frequency identification</topic><topic>Scanners</topic><topic>Software</topic><topic>Software development tools</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Eyahanyo, Felix</creatorcontrib><creatorcontrib>Rath, Thomas</creatorcontrib><creatorcontrib>1. Leibniz University of Hannover, Institute of Horticultural Production Systems, Biosystems Engineering Section, Herrenh鋟ser Stra遝 2, 30419 Hannover, Germany</creatorcontrib><creatorcontrib>2. University of Applied Sciences Osnabr點k, Biosystems Engineering Laboratory (BLab), Oldenburger Landstra遝 24, 49090 Osnabr點k, Germany</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>East & South Asia Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><jtitle>International journal of agricultural and biological engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Eyahanyo, Felix</au><au>Rath, Thomas</au><aucorp>1. Leibniz University of Hannover, Institute of Horticultural Production Systems, Biosystems Engineering Section, Herrenh鋟ser Stra遝 2, 30419 Hannover, Germany</aucorp><aucorp>2. University of Applied Sciences Osnabr點k, Biosystems Engineering Laboratory (BLab), Oldenburger Landstra遝 24, 49090 Osnabr點k, Germany</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of manual and automatic barcode detection in rough horticultural production systems</atitle><jtitle>International journal of agricultural and biological engineering</jtitle><date>2019-11-01</date><risdate>2019</risdate><volume>12</volume><issue>6</issue><spage>169</spage><epage>176</epage><pages>169-176</pages><issn>1934-6344</issn><eissn>1934-6352</eissn><abstract>Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success. Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner, and factors such as speed, angle of inclination of the barcode, damage to the barcode and dirt on the barcode. Furthermore, laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming, which leading to reduced productivity. Therefore, an automated image-based barcode detection system to help solve the aforementioned problems was proposed. Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company. The images were analyzed with a specific algorithm developed with the software tool Halcon. Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.</abstract><cop>Beijing</cop><pub>International Journal of Agricultural and Biological Engineering (IJABE)</pub><doi>10.25165/j.ijabe.20191206.4762</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1934-6344 |
| ispartof | International journal of agricultural and biological engineering, 2019-11, Vol.12 (6), p.169-176 |
| issn | 1934-6344 1934-6352 |
| language | eng |
| recordid | cdi_proquest_journals_2335162402 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Agricultural production Algorithms Automation Bar codes Dirt Experiments Flowers Horticulture Image detection Inclination angle Laboratories Lasers Localization Morphology Nurseries Radio frequency identification Scanners Software Software development tools |
| title | Comparison of manual and automatic barcode detection in rough horticultural production systems |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T10%3A18%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Comparison%20of%20manual%20and%20automatic%20barcode%20detection%20in%20rough%20horticultural%20production%20systems&rft.jtitle=International%20journal%20of%20agricultural%20and%20biological%20engineering&rft.au=Eyahanyo,%20Felix&rft.aucorp=1.%20Leibniz%20University%20of%20Hannover,%20Institute%20of%20Horticultural%20Production%20Systems,%20Biosystems%20Engineering%20Section,%20Herrenh%E9%8B%9Fser%20Stra%E9%81%9D%202,%2030419%20Hannover,%20Germany&rft.date=2019-11-01&rft.volume=12&rft.issue=6&rft.spage=169&rft.epage=176&rft.pages=169-176&rft.issn=1934-6344&rft.eissn=1934-6352&rft_id=info:doi/10.25165/j.ijabe.20191206.4762&rft_dat=%3Cproquest_cross%3E2335162402%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2335162402&rft_id=info:pmid/&rfr_iscdi=true |