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Lane line reconstruction method based on Bezier curve

A lane line and curve technology is applied in the field of lane line reconstruction based on Bézier curve to achieve the effect of improving real-time performance and accuracy, improving adaptability and improving accuracy

Inactive Publication Date: 2013-06-12
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems of complex environment adaptability, curve fitting accuracy and real-time performance in lane line reconstruction, the present invention proposes a lane line reconstruction method based on Bézier curves

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  • Lane line reconstruction method based on Bezier curve
  • Lane line reconstruction method based on Bezier curve
  • Lane line reconstruction method based on Bezier curve

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Embodiment Construction

[0044] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0045] Lane line recognition is one of the foundations of lane keeping, lane departure warning and autonomous navigation in intelligent vehicle safety assisted driving systems. The reconstruction of the lane line is not only to identify the position of the lane line in the image, but also to accurately fit the lane line with a specific curve model, so as to provide important parameter support such as road curvature for the subsequent decision-making module.

[0046] The present invention provides a lane line reconstruction method based on Bézier curves, which is used in a vision-based safety driving assistance system, and the reconstructed lane line information provides parameter support for a decision-making unit. The present invention can better adapt to complex environments such as illumination changes, road shadows, lane line discontinuities, obstacles, e...

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Abstract

The invention provides a lane line reconstruction method based on Bezier curve and used in the field of safe auxiliary driving of intelligent vehicles. The method provided by the invention comprises the following steps: searching the position of a starting block of a lane line in images inside an interested region on the basis of gradient characteristic and grayness characteristic, extending the searching in a block form, introducing a lane line intermittent searching mechanism and a curve searching mechanism, so as to achieve intermit and curve recognition; carrying out self-adaptive binaryzation treatment to all recognized blocks respectively so as to obtain points on the lane line; and respectively adopting one or two secondary Bezier curve fitting lane lines according to degree of crook of lane line. The method provided by the invention can well adapt to complex environment such as lighting variation, road shadow, lane line interruption, barriers and the like, pretreatment to images is not required, the real-time performance is improved, segmental Bezier curve fitting lane lines are adopted for improving the accuracy of variable camber curve reconstruction.

Description

technical field [0001] The invention belongs to the field of safe driving assistance for intelligent vehicles, and relates to a method for reconstructing lane lines based on Bézier curves. Background technique [0002] Throughout the history of automobile development, research on safety issues has always been a top priority. Especially in recent years, how to improve traffic safety has become an urgent social problem to be solved. The focus of automotive safety research has evolved from passive safety with collision safety as the core to active safety with collision prevention as the core. Many countries and international automotive electronics companies have already launched a number of research programs to find new technologies to improve safety and reduce accidents . Therefore, the concept of intelligent vehicle (Intelligent Vehicle) came into being and became one of the key technologies of intelligent transportation system (Intelligent Transportation System). As an im...

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Application Information

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IPC IPC(8): G06F17/30
Inventor 徐国艳高峰丁能根黄小云邢龙龙刘建行
Owner BEIHANG UNIV
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