Lane line identification method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a lane line identification method and device, equipment and a storage medium, and the method comprises the steps: obtaining a video, and determining the attribute parameters of the lane line according to the video frame information in the video, and enabling the attribute parameters of the lane line to comprise the type of the lane line, the stability of the lane line and the position of the lane line; determining attribute parameters of historical frame lane lines and attribute parameters of future frame lane lines according to the attribute parametersof the lane lines; and determining the attribute parameter of the current frame lane line according to the attribute parameter of the historical frame lane line and the attribute parameter of the future frame lane line. The invention relates to the technical field of image processing, and the attribute of the lane line of the current frame is reasoned by using the time sequence attribute of the front and rear frames of the video and the output of the segmentation model so that the judgment of the type of the lane line is more accurate, the lane line output result is more stable, and the sudden change of the type is reduced.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a method, device, equipment and storage medium for recognizing lane lines. Background technique [0002] The detection and recognition of lane lines is an indispensable part of the fields of automatic driving and intelligent traffic violation capture. Accurate detection of lane lines can assist vehicles to automatically drive in legal lanes, and smart traffic violations such as real-line lane changes, etc., have very high requirements for accurate identification of lane line types. At present, the commonly used lane recognition method uses the semantic segmentation model to obtain the mask of the lane line, and determines the type of the lane line by the category of the pixel in the mask area. [0003] In the prior art, the number of pixels to be processed is reduced by extracting candidate feature points representing the centerline of the lane line. By analyzi...

AI Technical Summary

Problems solved by technology

[0004] At present, in the market, the reliability of the detection of lane lines is low, and irreparable errors often occur in the application.

In addition, the lane line will be blocked by obstacles in the real scene, so the lane line information cannot be obtained accurately, and the lane line information is unstable during the recognition process

Images