Lane line clustering method and device

A clustering method and lane line technology, applied in the field of image processing, can solve problems such as poor clustering effect in complex scenes and affecting the accuracy of lane line recognition results

Active Publication Date: 2020-09-22
NAVINFO
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention provides a lane line clustering method and device to overcome the poor clustering effect of the lane line clustering method in the prior art on complex scenes such as Y-shaped and V-shaped roads, which affects the identification of lane lines The problem with the accuracy of the results

Method used

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  • Lane line clustering method and device
  • Lane line clustering method and device

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Experimental program
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Embodiment 1

[0033] An embodiment of the present invention provides a lane line clustering method, such as figure 1 As shown, the lane line clustering method includes:

[0034] Step S1: Obtain the feature image of the lane line, and form a set of feature points according to the preset rules from the pixels in the feature image of the lane line. Specifically, in practical applications, the lane line feature image is a segmentation result image obtained by segmenting the image containing the lane line by pixel, and the preset rule is to divide the lane line feature image by row from bottom to top according to the pixel points. Grouping and sorting constitutes a set of feature points.

[0035] Step S2: Select feature point groups from the feature point set sequentially according to preset conditions, and horizontally cluster the feature point groups to generate cluster groups. Specifically, in practical applications, the preset condition is to sequentially select feature point groups from t...

Embodiment 2

[0073] An embodiment of the present invention provides a lane line clustering device, such as Figure 7 As shown, the lane line clustering device includes:

[0074] The first processing module 1 is used to obtain the lane line feature image, and the pixel points in the lane line feature image form a feature point set according to preset rules. For details, refer to the relevant description of step S1 in Embodiment 1.

[0075] The second processing module 2 is used to sequentially select feature point groups from the feature point set according to preset conditions, and carry out horizontal clustering to the feature point groups to generate each cluster group. For details, refer to the relevant description of step S2 in Embodiment 1.

[0076] The third processing module 3 is used to calculate the cluster center of each cluster group respectively. For details, refer to the relevant description of step S3 in Embodiment 1.

[0077] The fourth processing module 4 is used to upd...

Embodiment 3

[0080] An embodiment of the present invention provides a non-transitory computer storage medium, the computer storage medium stores computer-executable instructions, and the computer-executable instructions can execute the lane line clustering method in any of the above-mentioned method embodiments, wherein the above-mentioned storage medium It can be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (Flash Memory), a hard disk (Hard DiskDrive, abbreviation: HDD) Or a solid-state drive (Solid-State Drive, SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memories.

[0081] Those skilled in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware, and the programs can be stored in a computer-readable storage medium. , may include...

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Abstract

The embodiment of the invention provides a lane line clustering method and device, and the method comprises the steps: obtaining a lane line feature image, and enabling pixels in the lane line featureimage to form a feature point set according to a preset rule; sequentially selecting feature point groups from the feature point set according to a preset condition, and performing transverse clustering on the feature point groups to generate clustering groups; respectively calculating a clustering center of each clustering group; and updating the lane lines in the existing lane line set according to a preset lane line reservation condition and a relationship between each clustering center and the existing lane line set, and returning to the step of carrying out transverse clustering on the feature point groups in the feature point set according to a preset condition to generate clustering groups until the feature point set is traversed to obtain a clustering result of the lane line feature image. The clustering method provided by the invention has good clustering speed and robustness, has a good clustering effect on Y-shaped and V-shaped roads, and further improves the accuracy of alane line recognition result.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a lane line clustering method and device. Background technique [0002] The vehicle automatic driving system can realize the real-time evaluation and decision-making of the safety status of the vehicle during the driving process by sensing the vehicle's own operating status and driving environment information in real time, so as to realize the intervention in the driving process and even realize unmanned driving. Lane lines are the most basic traffic signs in the road driving environment, and they are also the most basic constraints when the car is driving. The lane line recognition system based on machine vision is an important part of the intelligent transportation system. It is widely used in lane departure warning (Lane Departure Warning, LDW), adaptive cruise system (Adaptive Cruise Control, ACC), lane keeping System, LKS) and self-driving (Self-Driving) an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/588G06F18/23213
Inventor 周文龙
Owner NAVINFO
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