Lane marking detection method, device, electronic equipment and storage medium

A lane line detection, lane line technology, applied in the direction of instruments, biological neural network models, calculations, etc., can solve the problems of poor robustness and low accuracy, and achieve reduced interference, improved accuracy and quasi-call rate, and improved Effects of Robustness and Precision
CN110232368BActive Publication Date: 2021-08-24BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
Publication Date
2021-08-24

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Abstract

The present application proposes a lane marking detection method, device, electronic equipment and storage medium. Wherein, the method includes: inputting the acquired image to be detected into a preset target detection model, obtaining first detection information and second detection information of each grid in the image; Second, the detection information is subjected to non-maximum value suppression processing to obtain the position and category of each lane line boundary point in the image, the position of each lane center point, the corresponding lane width and the lane line category; according to each lane line boundary point in the image The location and category of each lane center point, the lane width corresponding to each lane center point, and the lane line category determine the lane line in the image and the category of each lane line. Therefore, through this lane line detection method, not only the accuracy and accuracy of lane line detection are improved, but also the robustness and accuracy of lane line type detection are improved.
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Description

technical field

[0001] The present application relates to the field of computer application technology, and in particular to a lane line detection method, device, electronic equipment and storage medium. Background technique

[0002] Today, in autonomous driving scenarios, lane lines, as important static semantic information, are of great significance to driving decisions, and the virtual and real category information of lane lines is of great significance to driving decisions.

[0003] In related technologies, traditional lane line detection methods mostly use traditional feature extraction methods to extract the visual features of the dashed and solid lines of the lane line, so as to judge whether the lane line is virtual or solid. However, this kind of lane line category detection method based on feature extraction, due to insufficient feature representation, is likely to cause poor robustness in judging the virtual and real lane line categories, and it cannot give the gr...

Claims

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