A lane line recognition method, device, equipment and medium

By receiving images and utilizing a pre-trained recognition model, combined with pixel adjacency relationships and adjustment vectors, the problem of inaccurate lane line recognition was solved, achieving high-accuracy recognition in multi-lane scenarios.

CN115311636BActive Publication Date: 2026-06-16CHINA TELECOM CLOUD TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA TELECOM CLOUD TECH CO LTD
Filing Date
2022-08-08
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

The inaccurate lane line recognition in existing technologies includes errors caused by outdated high-precision maps and the influence of the environment on radar recognition.

⚗Method used

By receiving an image and inputting it into a pre-trained recognition model, the recognition model outputs a target image carrying whether each pixel is a pixel on the lane line. Combining the adjacency relationship of the pixels and the adjustment vector, the lane line is determined, and the model is optimized through a training sample set to improve accuracy.

🎯Benefits of technology

It improves the accuracy of lane line recognition, reduces the workload of manually modifying high-precision maps, and ensures accurate lane line recognition in multi-lane scenarios.

✦ Generated by Eureka AI based on patent content.

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Abstract

The embodiment of the application provides a lane line identification method, device, equipment and medium, to solve the problem that the lane line identified in the prior art is not accurate. In the embodiment of the application, the electronic device determines whether each pixel point in the image is a pixel point on the lane line through the identification model, thereby improving the accuracy of lane line identification. In the embodiment of the application, after determining whether each pixel point in the image is a pixel point on the lane line, the electronic device determines each target pixel point that is a pixel point on the lane line and whose adjacent pixel points are pixel points on the lane line, and determines the lane line in the image according to each target pixel point, thereby further improving the accuracy of lane line identification.
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