Depth image based pavement detection system

Abstract

The invention discloses a depth image based pavement detection system. The system comprises a computer, an analyzing and processing module, a kinect sensor, an inverter and a vehicle; the kinect sensor, the computer and the inverter are installed on the vehicle, and the inverter provides power for the computer and the inverter; the kinect sensor is used for acquiring pavement depth image data and transmits to the computer; and the computer calls the analyzing and processing module, analyzes and processes the obtained pavement depth image data to obtain unevenness and damage information, and displays and stores the unevenness and damage information. The pavement unevenness and damage information is obtained through pavement depth images. The system has the advantages of simple operation, convenient use and maintenance, time and money saving, and provision of picturesque pavement information for people.

Description

technical field [0001] The invention relates to a road surface detection system based on a depth image, belonging to the technical field of road surface information detection. Background technique [0002] Pavement quality has an important impact on driving comfort, safety, economy and road life cycle. The management and maintenance of pavement is inseparable from the detection of pavement information. Road surface information detection includes unevenness detection, damage detection, etc. [0003] At present, there are mainly two types of road surface roughness detection devices: response type and cross-section type. Responsive pavement roughness testing equipment is generally simple in structure and cheap in price, but it cannot directly obtain the profile curve shape of the pavement, and its detection values ​​are not time-stable and require frequent calibration. Section-type road surface roughness testing equipment can directly obtain the curve shape of the longitudin...

AI Technical Summary

Problems solved by technology

Responsive road surface roughness testing equipment is generally simple in structure and cheap in price, but it cannot directly obtain the profile curve shape of the road surface, and its detection values ​​do not have time stability, and frequent calibration is required

Section-type road surface roughness testing equipment can directly obtain the curve shape of the longitudinal section of the road surface, but the section-type road surface roughness testing equipment has a complex structure and is expensive, and most of them are discrete tests, that is, several section values ​​​​along the longitudinal direction are used to measure the overall The level of roughness of the road reflects only an approximate value

In addition, most of the current roughness detection devices can only measure the roughness; or integrate multiple measurement systems together to simultaneously measure other road surface information such as damage, ruts, etc.

However, the information between the systems is not shared, and there are problems of waste of resources and low efficiency.

[0004] The damage detection system is mostly based on the images obtained by the CCD camera, which is highly dependent on the external lighting conditions such as light intensity, light source orientation and occlusion, and there will be a lot of uneven lighting and shadows in the road surface image, which increases the difficulty of damage detection

At the same time, factors such as road markings will have a certain impact on the detection

In addition, the depth information, that is, the distance value, is lost when the camera converts the 3D scene into a 2D image through the imaging system

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