Difference between revisions of "JRA/objective1/task2"
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This will include communicating with other groups including Hannover and iDigBio. It may include field books. It may include training the software. | This will include communicating with other groups including Hannover and iDigBio. It may include field books. It may include training the software. | ||
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| + | Existing handwriting resources include: | ||
| + | [http://harvest.cals.ncsu.edu/chiro/about.html Chirographum historicum] | ||
| + | [https://www.idigbio.org/content/handwriting-samples-resources-where-are-they-what-next iDigBio Handwriting Samples and Resources Page] | ||
| + | [http://gpi.myspecies.info/content/botanists Global Plants Initiative Botanists] | ||
| + | [http://www.ville-ge.ch/musinfo/bd/cjb/auxilium/index.php Conservatoire et Jardin Botaniques Ville de Geneve Auxilium ad Botanicorum Graphicem] | ||
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=== Subtask 4: Review of automatic capture of character including colour, shape as well as exif data === | === Subtask 4: Review of automatic capture of character including colour, shape as well as exif data === | ||
This is currently outside scope but could be included if it becomes prioritised during the project. | This is currently outside scope but could be included if it becomes prioritised during the project. | ||
Revision as of 13:38, 10 September 2014
Contents
- 1 Task 2: Automatic metadata capture
- 1.1 Subtask 1: Review development of tools and workflows which incorporate automatic or semi-automatic metadata capture using OCR
- 1.2 Subtask 2: Review of development of NLP for parsing ocr text into Darwin core fields
- 1.3 Subtask 3: Review of development of Natural Handwriting Recognition (NHR) in workflows to automate the identification of collectors’ handwriting and to train software to recognise text for prioritised collectors
- 1.4 Subtask 4: Review of automatic capture of character including colour, shape as well as exif data
Task 2: Automatic metadata capture
Develop software that will automatically identify properties of an image. These data “facets” will be automatically captured without human intervention and provide categories of information that allow Users to easily search and browse virtual collections more effectively.
Specimen label data will be subjected to Optical Character Recognition (OCR) software to extract the text string
and research methods to improve the accuracy of OCR use on handwritten labels. OCR-extracted text collected
from handwritten labels will need to be subject to further processing and validation, such as via crowdsourcing
methodologies (objective 2).
Subtask 1: Review development of tools and workflows which incorporate automatic or semi-automatic metadata capture using OCR
This will include format, standards, Darwin Core, linking with other digitisation groups working on OCR. It may include registers, field books, card catalogues.
Subtask 2: Review of development of NLP for parsing ocr text into Darwin core fields
This is currently outside scope but could be included if it becomes prioritised during the project.
Subtask 3: Review of development of Natural Handwriting Recognition (NHR) in workflows to automate the identification of collectors’ handwriting and to train software to recognise text for prioritised collectors
This will include communicating with other groups including Hannover and iDigBio. It may include field books. It may include training the software.
Existing handwriting resources include:
Chirographum historicum
iDigBio Handwriting Samples and Resources Page
Global Plants Initiative Botanists
Conservatoire et Jardin Botaniques Ville de Geneve Auxilium ad Botanicorum Graphicem
Subtask 4: Review of automatic capture of character including colour, shape as well as exif data
This is currently outside scope but could be included if it becomes prioritised during the project.
