Expressway night license plate anti-dazzling snapshot method based on deep learning algorithm
A technology of deep learning and expressways, applied to devices using optical methods, calculations, computer components, etc., can solve the problems of driver's eye glare, high fill light brightness, and inability to see the road ahead, etc., to improve driving Safety, the effect of improving road traffic safety
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[0052] Anti-glare capture method of license plate at night based on deep learning algorithm, such as Figure 10 As shown, the snapping device 1 used in the snapping method is installed on the gantry 2; the gantry 2 is fixedly erected at the corresponding position along the expressway road 3; the snapping device 1 includes a fixed angle mounted on the gantry 2, and the reciprocating swing mechanism 20 that can swing back and forth within a certain angle; the camera assembly 10 includes a speed measuring camera 11 and a license plate recognition camera 12; the installation angles of the speed measuring camera 11 and the license plate recognition camera 12 can be the same or different; the reciprocating swing mechanism 20 is a crank rocker mechanism, the crank is connected to the drive motor, and the rocker is fixedly connected to the fill light 30 through bolts or buckles, so that the fill light 30 can follow the rocker within a certain angle. Reciprocating swing; the supplement...
Embodiment 2
[0070] In order to improve the speed at which the processor 50 processes images and further improve the longitude of car light recognition, a better implementation is: in the step b, the processor 50 first performs a preprocessing step on the photo image, and the preprocessing The steps include a Gamma correction step, a grayscale image step, a Gaussian blur step, and a ROI clipping step;
[0071] like Figure 5As shown, in the step of graying the picture, usually, the color of the light source of the car lights at night in the captured photo image is a white or yellow ring-shaped area, which is obviously different from the background of the road surface and other vehicles in the image. , in order to maintain the balance of the R, G, and B channels, the gray value is defined as:
[0072]
[0073] In the above formula, I is the gray value, and R, G, and B are the RGB brightness values of each pixel in the picture;
Embodiment 3
[0078] When using a speed measuring camera 11 to take pictures, it is impossible to distinguish the high and low beams of the vehicle. In some dangerous road conditions, when the gantry is required to further record the state of the vehicle's headlights, or when encountering a steep road section, it is difficult to identify the low beam. In view of the above situation, a better implementation is: the camera assembly 10 includes two speed cameras 11 with different installation heights and installation angles, one speed camera 11 has a low installation height and a small angle with respect to the horizontal plane , used to identify low beam lights, another speed camera 11 is installed at a high height and has a relatively large angle with respect to the horizontal plane; at least two photoelectric sensors 51 with different heights are arranged on the column of the gantry 2, and the signal of the photoelectric sensor 51 Line is connected with the signal input terminal of processor...
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