Segment-based pavement crack quantification

Accurate quantitative information of crack length and width is important for assessing the severity level of cracks and making accurate pavement maintenance decisions. Nevertheless, due to the noise and fluctuation at the crack edge of pavement image, itis difficult to precisely determine the edge correspondence of crack that is necessary for measuring the crack width at a specific pixel. Different automated or manually performed measurements are likely to yield different results at the same pixel. Instead of measuring the crack width on a pixel-by pixel basis, this paper presents an accurate and robust segment-based method for measuring crack width. Firstly, based on the distinctive curved structure of pavement crack, a structured edge detector is trained to obtain the confidence map of crack edges. Secondly, with the crack edge map, the morphological operation is used to extract the crack skeleton which characterizes the propagation of the crack. Adaptive segmentation of the crack skeleton is performed to partition a crack curve into crack segments. Each crack segment has the same width because its edges become almost parallel after the segmentation. Finally, combining the structured edge confidence and grayscale contrast at crack edges, an enhanced edge map of crack is proposed to measure the width of each crack segment by translating the skeleton towards both edges. A large number of experiments taken on the synthetic and real world pavement images demonstrate that the proposed method can accurately and robustly quantify various cracks with the average accuracy of 93.7% for crack width. It is promising for quantitative pavement condition assessment and maintenance.