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Lane line detection method based on threshold self-adaptive binaryzation and connected domain analysis

A connected domain analysis and lane line detection technology, applied in the field of lane line detection based on threshold adaptive binarization and connected domain analysis, can solve the problem of not being able to effectively remove the influence of noise such as road shadows and signs, and not fully utilizing lanes Line space characteristics, not fully applicable to dynamically changing traffic scenes, etc., to achieve the effects of easy installation, reducing road shadows, and reducing product costs

Active Publication Date: 2019-05-24
TIANJIN UNIV +1
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  • Summary
  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

However, the threshold used to determine the edge in these methods is a constant that needs to be manually set, which makes these algorithms not fully suitable for dynamically changing traffic scenarios.
[0003] For the refinement of edge features, the commonly used algorithms in the past include classic image processing algorithms such as threshold segmentation and Gaussian filter. These methods need to manually set the threshold, do not make full use of the spatial characteristics of lane lines, and cannot effectively remove The influence of noise such as shadows and signs on the road surface

Method used

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  • Lane line detection method based on threshold self-adaptive binaryzation and connected domain analysis
  • Lane line detection method based on threshold self-adaptive binaryzation and connected domain analysis
  • Lane line detection method based on threshold self-adaptive binaryzation and connected domain analysis

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Embodiment 1

[0051] An embodiment of the present invention provides a lane line detection method based on threshold adaptive binarization and connected domain analysis, see figure 1 , the method includes the following steps:

[0052] 101: Using the geometric information of the camera, divide the collected image into a road part and a non-road part;

[0053] 102: Convert the colored road image into a binary image through an adaptive binarization threshold;

[0054] 103: Perform connected domain analysis on the binary image, eliminate the interference of other factors, and detect the correct lane line;

[0055] 104: Use the geometric moments of the connected domain to fit a straight line to represent the lane line.

[0056] In summary, through the above steps 101 to 104, the embodiment of the present invention utilizes the feature that lane line pixels occupy a fixed proportion in the grayscale image to realize threshold adaptive binarization, and according to the connected domain of the l...

Embodiment 2

[0058] The scheme in embodiment 1 is further introduced below in conjunction with specific calculation formulas and examples, see the following description for details:

[0059] 1. Lane image extraction

[0060] 1. Capture image

[0061] In order to realize the function of assisted driving, the camera should be installed on the vehicle to capture the road surface image, and ensure that the vehicle is driving in the correct lane by measuring the lane boundary. The installation of the camera involves three parameters: the installation position of the camera, the height of the installation of the camera and the tilt angle of the camera lens.

[0062] In order to make the lane to be detected approximately appear in the central part of the image to be detected, the central axis of the camera and the vehicle should be on the same plane. The installation height and lens angle can be adjusted according to the actual height of the vehicle and the resolution of the camera, as long as th...

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Abstract

The invention discloses a lane line detection method based on threshold self-adaptive binaryzation and connected domain analysis, and the method comprises the steps: dividing a collected image into aroad part and a non-road part through the geometric information of a camera; converting the color road image into a binary image through an adaptive binarization threshold value; subjecting the binaryimage to connected domain analysis, interference of other factors is eliminated, and detecting a correct lane line; and fitting a straight line by utilizing the geometric moment of the connected domain to represent a lane line. Threshold self-adaption binaryzation is achieved by utilizing the characteristic that lane line pixels occupy a fixed proportion in the gray level image, a connected domain screening method is designed according to the characteristics of the connected domains of the lane line part, and the lane line detection accuracy is greatly improved on the premise that the speed is guaranteed.

Description

technical field [0001] The invention relates to the field of lane line detection, in particular to a lane line detection method based on threshold adaptive binarization and connected domain analysis. Background technique [0002] Lane line detection is a basic task of locating lane lines in order to implement vehicle assisted driving algorithms. Lane line detection can be roughly divided into two parts: feature detection and feature refinement. Edge is one of the most widely used features in lane representation and detection. Among the existing open source algorithms, the Canny algorithm is commonly used by detecting pixels with strong gradient amplitudes, and edge features are extracted using gradient direction information. A bootable Gaussian filter. However, the thresholds used to determine edges in these methods are constants that need to be manually set, which makes these algorithms not fully suitable for dynamically changing traffic scenes. [0003] For the refineme...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/34
CPCY02T10/40
Inventor 褚晶辉王学惠王鹏孙立宪李敏
Owner TIANJIN UNIV
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