Since there always exist constraints in reinforced concrete structures and buildings deteriorate overtime, cracking seems unavoidable and appears in all types of structures, for example, concrete wall, beam, slab, and brick walls (Figure 1). The reason is that when cracks are developed and propagate, they tend to cause the reduction in the effective loading area which brings about the increase of stress and subsequently failure of the concrete or other structures. IntroductionĬracks are of major concern for ensuring the safety, durability, and serviceability of structures. Therefore, the constructed model can be a useful tool for building management agencies and construction engineers in the task of structure maintenance. Experimental results point out that the integration of M2GLD and the Otsu method, followed by other shape analysis algorithms, can successfully detect crack defects in digital images. The goal of this gray intensity adjustment method is to meliorate the accuracy of the crack detection results. In the new model, a gray intensity adjustment method, called Min-Max Gray Level Discrimination (M2GLD), is proposed to preprocess the image thresholded by the Otsu method. This study establishes an intelligent model based on image processing techniques for automatic crack recognition and analyses.
The manual process of crack detection is painstakingly time-consuming and suffers from subjective judgments of inspectors. The detection of cracks is a crucial task in monitoring structural health and ensuring structural safety.
0 kommentar(er)
