The algorithm of accelerated cracks detection and extracting skeleton by direction chain code in concrete surface image

Abstract

Due to concrete surface roughness, uneven illumination, shadows, complex background and other disruptive factors, the traditional image processing-based concrete crack detection method cannot accurately detect concrete cracks, especially unclear ones and some tiny ones. The crack detection method based on the percolation model, which fully considered the low brightness and slenderness of the cracks, can accurately detect unclear and tiny cracks. But this method is time-consuming, and in some cases, it may cause fractures on the detected cracks. In order to solve these problems, this paper proposed an improved algorithm of image crack inspection based on the percolation model, which can reduce processing time through reducing the number of percolated pixels. To reconnect the fractured cracks, this method extracts the skeleton of cracks first by using an algorithm of skeleton extraction based on direction chain code. Then this paper proposed a region extension-based algorithm to reconnect part of the fractured cracks. Experimental results showed that this algorithm can significantly accelerate crack detection and maintain high detection precision.

Keywords:

• Crack detection
• Percolation model
• Region extension
• Direction chain code
• De-noise

Acknowledgements

This work is supported by Chongqing Basic and Frontier Research Project [grant number cstc2015jcyjB0269 and cstc2014jcyjA1347], Chongqing Science and Technology Research Project of Chongqing Municipal Education Commission [grant number KJ1402002] and Outstanding Achievements Transformation Projects of University in Chongqing [grant number KJZH14219]. The authors wish to thank the associate editors and anonymous reviewers for their valuable comments and suggestions on this paper.

ORCID

Z. Qu http://orcid.org/0000-0001-7013-4854