e detection of cracks is a crucial task in monitoring structural health and ensuring structural safety. e manual process of crack detection is painstakingly time-consuming and suffers from subjective judgments of inspectors. is study establishes an intelligent model based on image processing techniques for automatic crack recognition and analyses. 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. e goal of this gray intensity adjustment method is to meliorate the accuracy of the crack detection results. 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. erefore, the constructed model can be a useful tool for building management agencies and construction engineers in the task of structure maintenance.
Also using the gray information, Nhat-Duc REF proposed a gray intensity adjustment method, which improved the detection results of cracks by adjusting gray intensity.
Detection of Surface Crack in Building Structures Using Image Processing Technique with an Improved Otsu Method for Image Thresholding
Advances in Civil Engineering
Engineering