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Proceedings Paper

Tiled fuzzy Hough transform for crack detection
Author(s): Kanapathippillai Vaheesan; Chanjief Chandrakumar; Senthan Mathavan; Khurram Kamal; Mujib Rahman; Amin Al-Habaibeh
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Paper 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%.

Paper Details

Date Published: 30 April 2015
PDF: 6 pages
Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 953411 (30 April 2015); doi: 10.1117/12.2182913
Show Author Affiliations
Kanapathippillai Vaheesan, Huawei Technologies Co., Ltd. (Sri Lanka)
Chanjief Chandrakumar, Univ. of Peradeniya (Sri Lanka)
Senthan Mathavan, Nottingham Trent Univ. (United Kingdom)
Khurram Kamal, National Univ. of Sciences and Technology (Pakistan)
Mujib Rahman, Brunel Univ. (United Kingdom)
Amin Al-Habaibeh, Nottingham Trent Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 9534:
Twelfth International Conference on Quality Control by Artificial Vision 2015
Fabrice Meriaudeau; Olivier Aubreton, Editor(s)

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