Fast detection and symptom analysis of cracks in highway asphalt pavement

Abstract

A method for real-time fast detection and symptom analysis of cracks in highway asphalt pavement is proposed. At the first step, the fissure characteristic of the acquired and de-noised pavement images is analyzed and then extracted by the method based on gray value comparison between the current pixel and its neighboring pixels, the false cracks are deleted by using the computed measurement of crack features, thus the true fissures are detected. The most important step is the symptom analysis of the cracks in the pavement image, all the data could be analyzed and be the basis for the agencies to remedy and manage the pavement. Quantities of images are processed and the results show that the proposed method can detect the pavement distress information actually, and has robustness and availability.