SAR: Stroke Authorship Recognition

Handle URI:
http://hdl.handle.net/10754/621413
Title:
SAR: Stroke Authorship Recognition
Authors:
Shaheen, Sara; Rockwood, Alyn; Ghanem, Bernard ( 0000-0002-5534-587X )
Abstract:
Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.
KAUST Department:
King Abdullah University of Science and Technology (KAUST); Thuwal Saudi Arabia
Citation:
Shaheen S, Rockwood A, Ghanem B (2015) SAR: Stroke Authorship Recognition. Computer Graphics Forum 35: 73–86. Available: http://dx.doi.org/10.1111/cgf.12733.
Publisher:
Wiley-Blackwell
Journal:
Computer Graphics Forum
Issue Date:
15-Oct-2015
DOI:
10.1111/cgf.12733
Type:
Article
ISSN:
0167-7055
Sponsors:
King Abdullah University of Science and Technology
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorShaheen, Saraen
dc.contributor.authorRockwood, Alynen
dc.contributor.authorGhanem, Bernarden
dc.date.accessioned2016-11-03T08:28:44Z-
dc.date.available2016-11-03T08:28:44Z-
dc.date.issued2015-10-15en
dc.identifier.citationShaheen S, Rockwood A, Ghanem B (2015) SAR: Stroke Authorship Recognition. Computer Graphics Forum 35: 73–86. Available: http://dx.doi.org/10.1111/cgf.12733.en
dc.identifier.issn0167-7055en
dc.identifier.doi10.1111/cgf.12733en
dc.identifier.urihttp://hdl.handle.net/10754/621413-
dc.description.abstractAre simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.en
dc.description.sponsorshipKing Abdullah University of Science and Technologyen
dc.publisherWiley-Blackwellen
dc.subjectAuthorship recognitionen
dc.subjectCategories and Subject Descriptors: image processing, computer vision - shape recognitionen
dc.subjectFraud detectionen
dc.subjectSketchen
dc.subjectSketch trainingen
dc.subjectStrokeen
dc.subjectStroke segmentsen
dc.subjectStyleen
dc.titleSAR: Stroke Authorship Recognitionen
dc.typeArticleen
dc.contributor.departmentKing Abdullah University of Science and Technology (KAUST); Thuwal Saudi Arabiaen
dc.identifier.journalComputer Graphics Forumen
kaust.authorShaheen, Saraen
kaust.authorRockwood, Alynen
kaust.authorGhanem, Bernarden
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