Method for detecting vehicle congestion
A vehicle congestion and vehicle technology, which is applied in traffic flow detection, image analysis, image enhancement, etc., can solve the problems of high energy consumption, long time consumption, and high parameter accuracy requirements, and achieves high efficiency, fast speed, and simple judgment method Effect
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Embodiment 2
[0039] The difference between this embodiment and Embodiment 1 is that: step (d) in the detection area, if the vehicle is not detected for 50 consecutive frames, it indicates that the vehicle has left the detection area. Reason: If the detection rate is 0.5, then the probability of not detecting the vehicle for 50 consecutive frames is 0.5 50 , the probability is very small.
Embodiment 3
[0041] In described step (b), the mode that this vehicle is tracked can adopt existing mode, but in the present embodiment, specific mode is as follows:
[0042] (b0) Collect infrared image models of vehicles under different weather conditions, carry out learning and training through algorithms, and obtain network models for recognition. This step can be set as required.
[0043] (b1) Through the method of deep learning, the type recognition is carried out on the images in the detection area acquired by the passive infrared thermal imager, all vehicles and types are detected, the outer edge of the vehicle is marked, and the center coordinates (x, y) of the vehicle are calculated and The length and width of the vehicle (h, w);
[0044] (b2) Analyzing all vehicles identified in the previous N frames of images, and all vehicle information in the identified current frame images, wherein N is an adjustment parameter, and the value range of N is 1
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