Smart city road pavement detection method and system based on computer vision

Abstract

The invention relates to the field of road pavement detection, in particular to a smart city road pavement detection method and system based on computer vision. The method comprises the steps of acquiring a reference image and a comparison image of a to-be-detected pavement area, and pre-processing the reference image and the comparison image; performing edge detection on the reference image to obtain each edge region of the reference image; and based on each edge region of the reference image, matching the pixel points of the reference image and the comparison image, and determining the flatness condition of the to-be-detected pavement according to the matching result of the pixel points. According to the invention, the real-time detection of the flatness of the road pavement is realized, the accuracy of road detection is improved, and the time used for road pavement detection is shortened at the same time.

Description

technical field [0001] This application relates to the field of road pavement detection, in particular to a computer vision-based smart city road pavement detection method and system. Background technique [0002] With the rapid development of society, the number of vehicles in cities has also increased, but road safety has gradually become an issue worthy of attention. Among them, the smoothness of the road has a serious impact on the driving of the vehicle, especially at night, when the car is driving on the uneven road, it will bring great trouble to the driver, and even cause traffic accidents. At present, most of the roads in small cities have unevenness, which will cause bumps and other phenomena in the driving process of the vehicle. In severe cases, it will cause damage to the chassis and bumpers of the vehicle, wasting a lot of time and money. [0003] At present, road detection is usually carried out by human detection or sensor detection, which has great limitati...

AI Technical Summary

Problems solved by technology

Among them, the smoothness of the road has a serious impact on the driving of the vehicle, especially at night, when the car is driving on the uneven road, it will bring great trouble to the driver, and even cause traffic accidents.

At present, most of the roads in small cities have unevenness, which will cause bumps and other phenomena in the driving process of the vehicle. In severe cases, it will cause damage to the chassis and bumpers of the vehicle, wasting a lot of time and money

[0003] At present, road detection is usually carried out by human detection or sensor detection, which has great limitations and low accuracy. Human detection will waste a lot of manpower and material resources, and it is prone to false detection, missed detection, etc., and the real-time performance is low; hardware equipment such as sensors The cost is high, and the external environment is relatively complex. Under the influence of the external environment, hardware devices such as sensors are prone to failure, resulting in untimely detection or inaccurate detection results.

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