Tiled fuzzy Hough transform for crack detection

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Vaheesan, K ; Chandrakumar, C ; Mathavan, S ; Kamal, K ; Rahman, M ; Al-Habaibeh, A (2015)

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%.
  • References (4)

    [1] "Flexible Pavement Maintenance and Rehabilitation," in Australian Asphalt Pavement Association, 2010.

    [2] Chambon, S., "Detection of Points of Interest for Geodesic Contours - Application on Road Images for Crack Detection," in VISAPP, 2011, pp. 210-213.

    [3] Zou, C., Cao, Y., Li, Q., Mao, Q., and Wang, S., "CrackTree: Automatic crack detection from pavement images," in Pattern Recognition Letters 33, 2012, pp. 227-238.

    [4] Cheng, H., and Miyojim, M., Automatic Pavement distress detection system, Journal of In-formation sciences, Vol.,108(July 1998), pp 219-240.

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