Lane line detection method and device
A technology for lane line detection and images to be detected, which is applied to instruments, character and pattern recognition, computer components, etc., and can solve problems such as inaccuracy and inaccurate number of white pixels
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Embodiment 1
[0100] See Figure 4 , is a flowchart of an embodiment of the lane line detection method of the present application, including the following steps:
[0101] Step 401: Determine the gradient image of the image to be detected.
[0102] In the embodiment of the present application, the road image collected by the camera can be used as the image to be detected, or the region of interest can be delineated on the road image, and the part of the image corresponding to the region of interest can be used as the image to be detected. Not limiting.
[0103] Those skilled in the art can understand that the region of interest can be determined on the road image in a variety of ways, for example, the region of interest can be framed on the road image by manual frame selection, and for example, the region of interest can be determined by a preset height Proportion (such as the lower 3 / 4 part) intercepts the region of interest on the road image. For another example, the part below the vanis...
Embodiment 2
[0145] See Figure 5 , is a flow chart of another embodiment of the lane line detection method of the present application, the Figure 5 The shown method focuses on the process of determining the binarization threshold according to the gradient value of the pixel point in the gradient image and the first setting condition, including the following steps:
[0146] Step 501: Determine a data set composed of gradient values of all pixels in the gradient image as a target data set.
[0147] In the embodiment of the present application, firstly, the data set composed of the gradient values of all pixels in the gradient image is determined as the target data set. For example, assuming that there are 256 pixels in the gradient image, the target data set includes 256 elements.
[0148] Step 502: Determine the average gradient value, minimum value, and maximum value of the gradient values in the target data set, and set the average gradient value as a gradient parameter.
[0149...
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