Using data mining for digital ink recognition: Dividing text and shapes in sketched diagrams

Show simple item record Blagojevic, Rachel en Plimmer, Beryl en Grundy, John en Wang, Yong en 2012-03-12T23:32:58Z en 2011-10 en
dc.identifier.citation COMPUTERS & GRAPHICS-UK 35(5):976-991 01 Oct 2011 en
dc.identifier.issn 0097-8493 en
dc.identifier.uri en
dc.description.abstract The low accuracy rates of text–shape dividers for digital ink diagrams are hindering their use in real world applications. While recognition of handwriting is well advanced and there have been many recognition approaches proposed for hand drawn sketches, there has been less attention on the division of text and drawing ink. Feature based recognition is a common approach for text–shape division. However, the choice of features and algorithms are critical to the success of the recognition. We propose the use of data mining techniques to build more accurate text–shape dividers. A comparative study is used to systematically identify the algorithms best suited for the specific problem. We have generated dividers using data mining with diagrams from three domains and a comprehensive ink feature library. The extensive evaluation on diagrams from six different domains has shown that our resulting dividers, using LADTree and LogitBoost, are significantly more accurate than three existing dividers. en
dc.language EN en
dc.publisher Pergamon en
dc.relation.ispartofseries Computers & Graphics en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from en
dc.rights.uri en
dc.subject Sketch tools en
dc.subject Recognition algorithms en
dc.subject Sketch recognition en
dc.subject Pen-based interfaces en
dc.title Using data mining for digital ink recognition: Dividing text and shapes in sketched diagrams en
dc.type Journal Article en
dc.identifier.doi 10.1016/j.cag.2011.07.002 en
pubs.issue 5 en
pubs.begin-page 976 en
pubs.volume 35 en
dc.rights.holder Copyright: Elsevier en
pubs.end-page 991 en
dc.rights.accessrights en
pubs.subtype Article en
pubs.elements-id 228230 en Science en Statistics en
dc.identifier.eissn 1873-7684 en
pubs.number 5 en
pubs.record-created-at-source-date 2012-02-21 en

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