Detection method and device
A detection method and road surface detection technology, which is applied in the field of image processing, can solve problems such as insufficient robustness of road detection algorithms, and achieve the effect of solving roadside shadow problems
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Embodiment 1
[0070] Embodiment 1: a kind of detection method.
[0071] refer to Figure 1 to Figure 5 As shown, a detection method specifically includes the following steps:
[0072] S1. Collect images through the on-board camera: position the camera directly in front of the vehicle, so that the information of the left and right lanes of the road ahead and the information of the feasible area of the road can be completely captured;
[0073] S2. Extracting the light source invariant features of the image: extracting the light source invariant features of the image mainly includes three steps:
[0074] S21, the RGB image I collected by step S1 RGB Calculate a light-invariant feature map I with reduced brightness influence, that is, a large amount of shadow attenuation, the effect is shown in Figure 2;
[0075] S22. Preliminarily extract the road surface area based on area growth based on the invariant characteristics of the light source;
[0076] S23. Calculate the light source invaria...
Embodiment 2
[0123] Embodiment 2: a detection device.
[0124] A detection device based on the detection method in embodiment 1, comprising:
[0125]Image acquisition module: use the CCD camera to capture the video image of the road surface, and transmit the data to the image processing module;
[0126] Wherein, the image acquisition module also includes: the CCD camera is positioned directly in front of the vehicle to completely capture the feasible area of the road surface, and transmit the image to the image processing module.
[0127] Image processing module: perform image processing on image data to obtain road surface detection results;
[0128] Among them, FPGA is equipped with image processing algorithm, which mainly extracts the light source invariant features of the image, extracts the background features of the image, and classifies the road surface based on similarity according to the light source invariant feature and background feature of the image, and sends the final det...
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