Improved percolation-based method for crack detection in concrete surface images

This paper presents a highly accurate and efficient method for crack detection using percolation-based image processing. The detection of cracks in concrete surfaces during the maintenance and diagnosis of concrete structures is important to ensure the safety of these structures. Recently, the image-based crack detection method has attracted considerable attention due to its low cost and objectivity. However, there are several problems in the practical application of image processing for crack detection since real concrete surface images have noises such as concrete blebs, stains, and shadings of several sizes. In order to resolve these problems, our proposed method focuses on the number of pixels in a crack and the connectivity of the pixels. Our method employs a percolation model for crack detection in order to consider the features of the cracks. Through experiments using real concrete surface images, we demonstrate the accuracy and efficiency of our method.