A method for detecting cracks in highway pavement

Abstract

A highway pavement crack detection method, by pre-extracting the highway pavement area of ​​interest in the image, detecting the image line segment endpoints that may be pavement cracks, and then using multi-scale processing combined with gradient histogram and support vector machine for classification, and finally Output the area information that is judged to be a road surface crack, and prompt the user. The video information of the invention is richer, the classification is more accurate, and the false alarm rate can be lower; it can adapt to a larger range and environment, and has a higher level of automatic processing, which can improve the accuracy of detection and improve the efficiency of detection and identification, and is more efficient than The traditional method is more stable and has higher anti-noise and anti-tilt capabilities; it solves the problems of high intensity of manual inspection work, limited by experience level, high probability of misjudgment and omission.

Description

technical field [0001] The invention relates to the technical field of automatic video detection, in particular to a method for detecting cracks on highway pavement. Background technique [0002] In recent years, the construction speed and operation scale of my country's high-grade highways have reached the world's leading level. However, with the increase of vehicle speed and the widespread use of heavy-duty vehicles, the excitation frequency of high-grade road subgrade systems has also become wider, and it is susceptible to high-frequency excitation and resonance, causing increased vibration and accelerated aging, which will affect road operation. quality and increase maintenance costs, and will accelerate the structural fatigue damage of pavement asphalt. If the damaged highway pavement is not found and repaired in time, the damage will be accelerated under the action of vehicle rolling, which will affect road comfort and even endanger driving safety. In this situation,...

AI Technical Summary

Problems solved by technology

[0003] However, due to the special problem of information loss caused by the projection of 3D information into 2D images in the process of video imaging, it is still difficult to understand scenes and identify problems based on video images.

At the same time, because the effect of image acquisition in practical applications is limited by the intensity and uniformity of the light and the interference of the complexity of the environment, it will be difficult to distinguish the pavement cracks to be detected from other areas of the pavement (such as figure 1 shown)

Images