A generalisable framework for saliency-based line segment detection

Article

Brown, M., Windridge, D. and Guillemaut, J. 2015. A generalisable framework for saliency-based line segment detection. Pattern Recognition. 48 (12), pp. 3993-4011. https://doi.org/10.1016/j.patcog.2015.06.015
TypeArticle
TitleA generalisable framework for saliency-based line segment detection
AuthorsBrown, M., Windridge, D. and Guillemaut, J.
Abstract

Here we present a novel, information-theoretic salient line segment detector. Existing line detectors typically only use the image gradient to search for potential lines. Consequently, many lines are found, particularly in repetitive scenes. In contrast, our approach detects lines that define regions of significant divergence between pixel intensity or colour statistics. This results in a novel detector that naturally avoids the repetitive parts of a scene while detecting the strong, discriminative lines present. We furthermore use our approach as a saliency filter on existing line detectors to more efficiently detect salient line segments. The approach is highly generalisable, depending only on image statistics rather than image gradient; and this is demonstrated by an extension to depth imagery. Our work is evaluated against a number of other line detectors and a quantitative evaluation demonstrates a significant improvement over existing line detectors for a range of image transformations

PublisherElsevier Science
JournalPattern Recognition
ISSN0031-3203
Publication dates
PrintDec 2015
Publication process dates
Deposited22 Apr 2016
Accepted25 Jun 2015
Output statusPublished
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Copyright Statement

© 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Additional information

Available online 6 July 2015

Digital Object Identifier (DOI)https://doi.org/10.1016/j.patcog.2015.06.015
Scopus EID2-s2.0-84941414018
LanguageEnglish
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