Lane line detection method, device and equipment and storage medium

A lane line detection and lane line technology, which is applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve the problems of high demand for computing resources and increased overall cost.

Active Publication Date: 2021-03-19
CHINA FIRST AUTOMOBILE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, most lane line detection methods use inverse perspective transformation, edge detection, Hough transform and other steps to detect lane lines, or use deep learning methods to detect lane lines by segmentation and clustering. There are many demands, and it is difficult to achieve the purpose of real-time detection on a lightweight embedded platform. If it is replaced with a platform with stronger computing power, the overall cost will increase

Method used

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  • Lane line detection method, device and equipment and storage medium
  • Lane line detection method, device and equipment and storage medium
  • Lane line detection method, device and equipment and storage medium

Examples

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Embodiment 1

[0051]figure 1 It is a flow chart of a lane line detection method provided by Embodiment 1 of the present invention. This embodiment is applicable to the detection of lane lines. The method can be executed by a lane line detection device, such as figure 1 As shown, the method specifically includes the following steps:

[0052] Step 110, extracting pixel points in the current image whose gradients are greater than a first threshold as a candidate point set; extracting pixel points in the current image whose gradients are greater than a second threshold as a candidate point set.

[0053] Wherein, the first threshold is greater than the second threshold. The current image may be an image around the vehicle collected by a camera installed on the vehicle.

[0054] Specifically, after the current image is obtained, the current image is first grayscaled, and then the pixels in the grayscaled image are traversed line by line, the gradient value of the traversed pixel is calculated, a...

Embodiment 2

[0078] figure 2 It is a schematic structural diagram of a lane line detection device provided in Embodiment 2 of the present invention. like figure 2 As shown, the device includes:

[0079] The point set determination module 210 is used for the pixel points whose gradient is greater than the first threshold in the current image as the candidate point set; extracts the pixels whose gradient is greater than the second threshold in the current image as the candidate point set; wherein the first threshold is greater than second threshold;

[0080] The first sub-point set acquisition module 220 is used to perform connected domain search on the candidate point set to obtain multiple sets of first sub-point sets;

[0081] The first lane line information acquisition module 230 is configured to perform lane line feature extraction on multiple sets of first sub-point sets, and obtain first lane line information corresponding to each first sub-point set;

[0082] The second lane li...

Embodiment 3

[0109] image 3 It is a schematic structural diagram of a computer device provided by Embodiment 3 of the present invention. image 3 A block diagram of a computer device 312 suitable for implementing embodiments of the invention is shown. image 3 The computer device 312 shown is only an example, and should not impose any limitation on the functions and scope of use of the embodiments of the present invention. Device 312 is a typical computing device for lane line detection functions.

[0110] like image 3 As shown, computer device 312 takes the form of a general-purpose computing device. Components of computer device 312 may include, but are not limited to: one or more processors 316, storage 328, bus 318 connecting various system components including storage 328 and processor 316.

[0111] Bus 318 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a loca...

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Abstract

The embodiment of the invention discloses a lane line detection method, device and equipment and a storage medium. The method comprises the following steps: extracting pixel points with gradients greater than a first threshold value in a current image as a candidate point set; carrying out connected domain search on the candidate point set to obtain a plurality of groups of first sub-point sets; lane line feature extraction is carried out on the multiple groups of first sub-point sets to obtain first lane line information; clustering the plurality of groups of first sub-point sets to obtain aplurality of groups of second sub-point sets, and updating second lane line information; determining candidate lane line information according to the set lane line information and the second lane lineinformation in the cache; matching the candidate lane line information with the third lane line information in the cache, and determining a displayable lane line according to a matching result; determining selectable points from the candidate point set or the alternative point set, and adding the selectable points into a point set corresponding to the displayable lane line to obtain a target point set; and performing curve fitting on the target point set to obtain a target lane line. The calculation resource quantity and cost can be reduced.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of driving assistance, and in particular to a lane line detection method, device, equipment and storage medium. Background technique [0002] With the rapid development of the times, car safety has become an indispensable part of life now, so more and more advanced driver assistance system functions are applied to vehicles, among which lane line detection is the most basic function. [0003] At present, most lane line detection methods use inverse perspective transformation, edge detection, Hough transform and other steps to detect lane lines, or use deep learning methods to detect lane lines by segmentation and clustering. There are many demands, and it is difficult to achieve the purpose of real-time detection on a lightweight embedded platform. If it is replaced with a platform with stronger computing power, the overall cost will increase. Contents of the invention [0004] Em...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/588G06F18/23G06F18/214
Inventor季加阳陈博尹荣彬张伟伟汤永俊郑正
OwnerCHINA FIRST AUTOMOBILE