Image-Based Crack Detection Using Crack Width Transform (CWT) Algorithm

This paper describes an image-based methodology for the detection of structural cracks in concrete. The conventional approach based on line enhancement filtering has problems associated with an inaccurate extraction of edge pixels. We therefore propose an edge-based crack detection technique consisting of five steps: crack width transform, aspect ratio filtering, crack region search, hole filling, and relative thresholding. In the first step, crack width transform, opposing edges are identified and classified as crack candidate pixels, and a width map is generated. In the second step, aspect ratio filtering, the width map generated is used to remove noise. In the next two steps, the method searches for and restores missing pixels. In the last step, relative thresholding, residual noise is removed through reclassification of crack regions based on image-adaptive thresholding. The performance of this technique was tested using synthetic and real images. The results show that the proposed technique has greater accuracy and consistency in measuring crack width compared with the conventional technique.