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A generalisable framework for saliency-based line segment detection

Brown, M, Windridge, D and Guillemaut, JY (2015) A generalisable framework for saliency-based line segment detection Pattern Recognition, 48 (12). pp. 3993-4011.

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Abstract

© 2015 The Authors. 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
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Brown, MUNSPECIFIEDUNSPECIFIED
Windridge, DUNSPECIFIEDUNSPECIFIED
Guillemaut, JYUNSPECIFIEDUNSPECIFIED
Date : 1 December 2015
Identification Number : 10.1016/j.patcog.2015.06.015
Additional Information : 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/).
Depositing User : Symplectic Elements
Date Deposited : 21 Aug 2015 15:57
Last Modified : 28 Sep 2016 15:04
URI: http://epubs.surrey.ac.uk/id/eprint/808261

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