A generalisable framework for saliency-based line segment detection

Brown, Mark, Windridge, David ORCID: https://orcid.org/0000-0001-5507-8516 and Guillemaut, Jean-Yves (2015) A generalisable framework for saliency-based line segment detection. Pattern Recognition, 48 (12) . pp. 3993-4011. ISSN 0031-3203 (doi:10.1016/j.patcog.2015.06.015)

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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

Item Type: Article
Additional Information: Available online 6 July 2015
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 19485
Notes on copyright: © 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/)
Useful Links:
Depositing User: David Windridge
Date Deposited: 22 Apr 2016 10:39
Last Modified: 01 Jun 2019 01:05
URI: https://eprints.mdx.ac.uk/id/eprint/19485

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