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.