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The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels
Abstract. At the Royal Botanic Garden Edinburgh (RBGE) the use of Optical Character Recognition (OCR) to aid the digitisation process has been investigated. This was tested using a herbarium specimen digitisation process with two stages of data entry. Records were initially batch-processed to add da...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Pensoft Publishers
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086207/ https://www.ncbi.nlm.nih.gov/pubmed/25009435 http://dx.doi.org/10.3897/phytokeys.38.7168 |
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author | Drinkwater, Robyn E. Cubey, Robert W. N. Haston, Elspeth M. |
author_facet | Drinkwater, Robyn E. Cubey, Robert W. N. Haston, Elspeth M. |
author_sort | Drinkwater, Robyn E. |
collection | PubMed |
description | Abstract. At the Royal Botanic Garden Edinburgh (RBGE) the use of Optical Character Recognition (OCR) to aid the digitisation process has been investigated. This was tested using a herbarium specimen digitisation process with two stages of data entry. Records were initially batch-processed to add data extracted from the OCR text prior to being sorted based on Collector and/or Country. Using images of the specimens, a team of six digitisers then added data to the specimen records. To investigate whether the data from OCR aid the digitisation process, they completed a series of trials which compared the efficiency of data entry between sorted and unsorted batches of specimens. A survey was carried out to explore the opinion of the digitisation staff to the different sorting options. In total 7,200 specimens were processed. When compared to an unsorted, random set of specimens, those which were sorted based on data added from the OCR were quicker to digitise. Of the methods tested here, the most successful in terms of efficiency used a protocol which required entering data into a limited set of fields and where the records were filtered by Collector and Country. The survey and subsequent discussions with the digitisation staff highlighted their preference for working with sorted specimens, in which label layout, locations and handwriting are likely to be similar, and so a familiarity with the Collector or Country is rapidly established. |
format | Online Article Text |
id | pubmed-4086207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Pensoft Publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-40862072014-07-09 The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels Drinkwater, Robyn E. Cubey, Robert W. N. Haston, Elspeth M. PhytoKeys Research Article Abstract. At the Royal Botanic Garden Edinburgh (RBGE) the use of Optical Character Recognition (OCR) to aid the digitisation process has been investigated. This was tested using a herbarium specimen digitisation process with two stages of data entry. Records were initially batch-processed to add data extracted from the OCR text prior to being sorted based on Collector and/or Country. Using images of the specimens, a team of six digitisers then added data to the specimen records. To investigate whether the data from OCR aid the digitisation process, they completed a series of trials which compared the efficiency of data entry between sorted and unsorted batches of specimens. A survey was carried out to explore the opinion of the digitisation staff to the different sorting options. In total 7,200 specimens were processed. When compared to an unsorted, random set of specimens, those which were sorted based on data added from the OCR were quicker to digitise. Of the methods tested here, the most successful in terms of efficiency used a protocol which required entering data into a limited set of fields and where the records were filtered by Collector and Country. The survey and subsequent discussions with the digitisation staff highlighted their preference for working with sorted specimens, in which label layout, locations and handwriting are likely to be similar, and so a familiarity with the Collector or Country is rapidly established. Pensoft Publishers 2014-05-19 /pmc/articles/PMC4086207/ /pubmed/25009435 http://dx.doi.org/10.3897/phytokeys.38.7168 Text en Robyn E. Drinkwater, Robert W. N. Cubey, Elspeth M. Haston http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Drinkwater, Robyn E. Cubey, Robert W. N. Haston, Elspeth M. The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels |
title | The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels |
title_full | The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels |
title_fullStr | The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels |
title_full_unstemmed | The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels |
title_short | The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels |
title_sort | use of optical character recognition (ocr) in the digitisation of herbarium specimen labels |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086207/ https://www.ncbi.nlm.nih.gov/pubmed/25009435 http://dx.doi.org/10.3897/phytokeys.38.7168 |
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