A road congestion detection method based on video image processing
A detection method and video image technology, applied in the direction of still image data retrieval, traffic flow detection, road vehicle traffic control system, etc., can solve the problems of low detection rate, poor real-time performance, poor processing ability in complex environments, etc., and achieve effective improvement sex, the effect of avoiding traffic accidents
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Embodiment 1
[0048] Embodiment 1: as figure 1 As shown, the specific steps of a road congestion detection method based on video image processing are:
[0049] Step1: Obtain the original image data R from the road monitoring system; the source of the original image data R can be the camera equipment (including but not limited to the gun camera and the dome camera) installed directly on the road, or the monitoring center has been deployed The streaming media platform can be real-time data from other road monitoring systems; raw data R includes pictures (single or multiple), videos and network streams.
[0050] Step2: Preprocess the original image data R to obtain the processed data R';
[0051] Step3: Analyze the characteristics of the processed data R′, extract its characteristic attributes Q, and the characteristic attributes Q include road structured information Q 1 and vehicle structured information Q 2 ; Use the internal private data type processed in Step 2 as a prototype, use the v...
Embodiment 2
[0084] Embodiment 2: as figure 2 As shown, in step Step2, different preprocessing methods will be performed according to the type of raw data R, and the specific processing is as follows:
[0085] If the type of the acquired original image data R is in the form of pictures, set the image correlation threshold γ to 0, that is, γ=0, and then set all the data in the original image data R as internal private data types, and perform Step3 and subsequent operations;
[0086] If the acquired original image data R is in the form of a video, set the image correlation threshold γ to 1, that is, γ=1, and then read each frame of the original image data R and convert it into a picture form, which is set as internal Private data types, and perform Step3 and subsequent operations on them;
[0087] If the type of the acquired original image data R is in the form of network streaming, set the image correlation threshold γ to 0.5, that is, γ=0.5, and open the buffer pool; then adopt the para...
Embodiment 3
[0089] Embodiment 3: When judging which lane the vehicle specifically belongs to in step Step4, there will be various situations, and the comprehensive road structured information Q is required. 1 and vehicle structured information Q 2For consideration, the extraction of key values refers to the data information required for judgment in different situations, such as determining the ownership of a vehicle based on the lane, assuming that the lane is a straight lane, and the vehicle changes lanes, passing the vehicle The color of the vehicle or the license plate and other body information to determine whether it is the same vehicle. If it is the same vehicle, the last position of the vehicle is used to determine the lane it belongs to; if there is a change in the direction of the lane, such as a turn, and The vehicle driving on this lane at the beginning changed lanes but did not turn accordingly, so the final position of the vehicle needs to be used as the criterion for judgm...
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Abstract
Description
Claims
Application Information
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