A Vehicle Measurement Method Based on Map Image

Abstract

The invention discloses a vehicle measurement method based on a map image, comprising: connecting a camera, determining a corresponding area on the map image according to the location information of the video image, and selecting a calibration object based on the summarized calibration object selection experience; selecting the calibration object respectively Feature points in the video scene and map image, and adaptively modify the transformation matrix; correct the scale of the map image based on the calculated distance and the distance measured by the ranging tool; detect and track vehicles through the improved YOLO algorithm and video jitter processing algorithm, Correct the real-time position and speed of the vehicle; finally save the vehicle characteristics, speed and real-time position, and upload it to the background server. Through the combination of the camera and the map image, the camera calibration can be completed without special calibration objects during calibration. It is simple and fast, without the need to waste extra manpower and material resources. By combining the improved YOLO algorithm and video jitter processing algorithm to reduce the misjudgment rate and measure more accurately Vehicle Information.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to a vehicle measurement method based on map images. Background technique [0002] As an all-weather reliable monitoring, video surveillance is more and more recognized by the society. It can provide users with more accurate characteristics of security threats, reduce the probability of false positives and false positives, and enable security departments to have enough time to detect potential threats. prepare for the threat. [0003] The current methods of measuring speed mainly include methods based on ground induction coils and methods based on camera calibration. Ground sense coil detection has the advantages of low price and fast detection speed, but it will cause great damage to the road, a large amount of preliminary engineering, and affect traffic; traditional camera calibration often obtains multiple pictures taken from different angles of the scene artificially, for...

AI Technical Summary

Problems solved by technology

Ground sense coil detection has the advantages of low price and fast detection speed, but it will cause great damage to the road, a large amount of preliminary engineering, and affect traffic; traditional camera calibration often obtains multiple pictures taken from different angles of the scene artificially, for some distant, It is not applicable to places with insufficient manpower. Some other improved camera calibration uses some special traffic signs and graphics composed of special buildings for camera calibration, but once the video does not have these special markings and graphics, it cannot be used. method

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