Tiled fuzzy Hough transform for crack detection

Vaheesan, K., Chandrakumar, C., Mathavan, S. ORCID: 0000-0001-7003-2874, Kamal, K., Rahman, M. and Al-Habaibeh, A. ORCID: 0000-0002-9867-6011, 2015. Tiled fuzzy Hough transform for crack detection. In: F. Meriaudeau and O. Aubreton, eds., Proceedings of SPIE: Twelfth International Conference on Quality Control by Artificial Vision 2015, Le Creusot, France, 3 June 2015. SPIE, p. 953411. ISBN 9781628416992

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Abstract

Surface cracks can be the bellwether of the failure of any component under loading as it indicates the component's fracture due to stresses and usage. For this reason, crack detection is indispensable for the condition monitoring and quality control of road surfaces. Pavement images have high levels of intensity variation and texture content, hence the crack detection is difficult. Moreover, shallow cracks result in very low contrast image pixels making their detection difficult. For these reasons, studies on pavement crack detection is active even after years of research. In this paper, the fuzzy Hough transform is employed, for the first time to detect cracks on any surface. The contribution of texture pixels to the accumulator array is reduced by using the tiled version of the Hough transform. Precision values of 78% and a recall of 72% are obtaining for an image set obtained from an industrial imaging system containing very low contrast cracking. When only high contrast crack segments are considered the values move to mid to high 90%.

Item Type: Chapter in book
Creators: Vaheesan, K., Chandrakumar, C., Mathavan, S., Kamal, K., Rahman, M. and Al-Habaibeh, A.
Publisher: SPIE
Date: 30 April 2015
Volume: 9534
ISSN: 0277786X
Identifiers:
NumberType
10.1117/12.2182913DOI
Divisions: Schools > School of Architecture, Design and the Built Environment
Depositing User: Linda Sullivan
Date Added: 27 Jul 2016 10:32
Last Modified: 07 Aug 2017 09:44
URI: http://irep.ntu.ac.uk/id/eprint/28223

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