Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/5614
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Leedham, Graham | en |
dc.contributor.author | Ma, Yang | en |
dc.contributor.author | Blumenstein, Michael | en |
dc.date.accessioned | 2010-04-19T09:14:00Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | International Journal of Pattern Recognition and Artificial Intelligence, 23(5), p. 1031-1051 | en |
dc.identifier.issn | 1793-6381 | en |
dc.identifier.issn | 0218-0014 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/5614 | - |
dc.description.abstract | Handwritten shorthand systems were devised to enable writers to record information on paper at fast speeds, ideally at the speed of speech. While they have been in existence for many years it is only since the 17th Century that widespread usage appeared. Several shorthand systems flourished in the first half of the 20th century until the introduction and widespread use of electronic recording and dictation machines in the 1970's. Since then, shorthand usage has been in rapid decline, but has not yet become a lost skill. Pitman shorthand has been shown to possess unique advantages as a means of fast text entry which is particularly applicable to hand-held devices in mobile environments. This paper presents progress and critical research issues for a Pitman/Renqun Shorthand Online Recognition System. Recognition and transcription experiments are reported which indicate that a correct recognition and transcription rate of around 90% is currently possible. | en |
dc.language | en | en |
dc.publisher | World Scientific Publishing Company | en |
dc.relation.ispartof | International Journal of Pattern Recognition and Artificial Intelligence | en |
dc.title | Handwritten Shorthand and its Future Potential for Fast Mobile Text Entry | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1142/S0218001409007405 | en |
dc.subject.keywords | Image Processing | en |
dc.subject.keywords | Computer Vision | en |
dc.subject.keywords | Artificial Intelligence and Image Processing | en |
local.contributor.firstname | Graham | en |
local.contributor.firstname | Yang | en |
local.contributor.firstname | Michael | en |
local.subject.for2008 | 080106 Image Processing | en |
local.subject.for2008 | 080199 Artificial Intelligence and Image Processing not elsewhere classified | en |
local.subject.for2008 | 080104 Computer Vision | en |
local.subject.seo2008 | 890299 Computer Software and Services not elsewhere classified | en |
local.subject.seo2008 | 810199 Defence not elsewhere classified | en |
local.subject.seo2008 | 810107 National Security | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | cleedham@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.identifier.epublicationsrecord | une-20100415-151057 | en |
local.publisher.place | Singapore | en |
local.format.startpage | 1031 | en |
local.format.endpage | 1051 | en |
local.identifier.scopusid | 69249087793 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 23 | en |
local.identifier.issue | 5 | en |
local.contributor.lastname | Leedham | en |
local.contributor.lastname | Ma | en |
local.contributor.lastname | Blumenstein | en |
dc.identifier.staff | une-id:cleedham | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:5746 | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Handwritten Shorthand and its Future Potential for Fast Mobile Text Entry | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Leedham, Graham | en |
local.search.author | Ma, Yang | en |
local.search.author | Blumenstein, Michael | en |
local.uneassociation | Unknown | en |
local.year.published | 2009 | en |
Appears in Collections: | Journal Article School of Science and Technology |
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