A stereovision-based crack width detection approach for concrete surface assessment

To quantitatively evaluate crack width of concrete structures surface, this paper presents a stereovision-based crack width detection method. Compared with the traditional visual inspection with single camera, this approach uses a pair of cameras to capture cracks images for recovering 3D coordinates of crack edge, and does not needs scale attached to concrete surface for converting measurement unit. A novel Canny-Zernike combination algorithm is utilized to obtain the image coordinates of crack edge in the left crack image, this combination algorithm can achieve 0.02 subpixel precision. The 3D coordinates of crack edge are acquired by projecting crack edge curve on concrete surface where cracks are located. The crack width is assessed by the minimum distance between two sides of crack edge. The detection tests are conducted on three concrete beams destroyed in static test, and the crack width of two inspection zones on each beam is acquired. Experimental results indicate that the stereovision-based crack width detection approach can accurately measure the crack width compared with the crack width gauge or the vernier calliper. This verifies the proposed method is applicable and useful for assessing the crack width of concrete surface.