Fast pavement disease detecting method based on image

Abstract

The invention discloses a fast pavement disease detecting method based on an image. According to the method, pavement diseases of various types can be detected fast. The method comprises the steps that a range sensor triggers a camera to carry out shooting, and a pavement gray level image is obtained in the running process of a vehicle; preprocessing such as downsampling and track area detection is carried out on the image; disease edge detection, disease boundary smoothing, disease area detection, connection, clustering and other disease detection processes are carried out; the disease detection result is output. The method has good geometric distortion and uneven brightness change resisting capacity in robustness, the pavement diseases can be detected fast, the pavement diseases of various types can be detected, the threshold valve can be flexibly adjusted according to actual needs, and detection precision and speed can be adjusted.

Description

technical field [0001] The invention belongs to the field of road surface disease detection, and relates to a fast image-based road surface disease detection method, in particular, it can perform detection with different accuracy and speed according to user requirements. Background technique [0002] With the continuous development of our country's economy, the role of transportation in the national economy and society is becoming more and more obvious, and the status is getting higher and higher. The expressway, which is the main artery of transportation, has developed rapidly. The construction and rise of expressways have provided people with efficient, convenient and safe new modes of transportation, driven economic and cultural exchanges between various regions, and are new economic growth points vigorously promoted by the country. At present, the mileage of expressways in my country ranks second in the world, and relatively complete road management regulations and syste...

AI Technical Summary

Problems solved by technology

At present, the mileage of expressways in my country ranks second in the world, and relatively complete road management regulations and systems have been established. The establishment of these systems effectively guarantees the scientific nature of maintenance; , supporting management as a complex system engineering, there are still many problems to be solved, especially the maintenance task of expressway, which has become one of the key factors to ensure its normal operation, if it can be found in the early stage of road surface disease, And formulate a reasonable maintenance strategy, then the maintenance cost of the road surface will be greatly reduced. How to quickly conduct a comprehensive investigation of the entire road surface and automatically locate the road surface disease area without affecting the normal traffic order has become a great reality. meaningful but intractable problem

[0003] In the past, the commonly used detection method was based on artificial vision to do on-site investigation and detection of diseases, but it could not well meet the requirements of the development of expressways. Driving, using eyes to detect diseases on the road, it takes a considerable amount of manpower or takes a long time to complete the investigation of a section of road; the accuracy is low, it is greatly affected by the environment and inspectors, and weather factors will be more seriously affected The perception of road surface diseases, the subjective factors of the inspectors will also interfere with the evaluation of road surface diseases; affect the traffic, when manually inspecting the road surface, in order to ensure the safety of the staff, it is necessary to frequently close the lane or road section, which will interfere with the use of the road; the inspection environment Dangerous, the staff has been carrying out detection work in semi-closed road sections for a long time (such as: some lanes are closed while the rest of the lanes are free to traffic), and the passing vehicles and discarded objects on the expressway pose a greater threat to it

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