Method for detecting lane lines based on grayscale estimation and cascade Hough transform

A technology of lane line detection and Hough transform, which is applied in computing, road network navigator, image data processing, etc., can solve the problems of camera parameter calibration and installation accuracy requirements are quite high

Inactive Publication Date: 2009-12-23
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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The disadvantage of this method is that the accuracy of camera parameter calibration and installation is quite high, because the transfor

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  • Method for detecting lane lines based on grayscale estimation and cascade Hough transform
  • Method for detecting lane lines based on grayscale estimation and cascade Hough transform
  • Method for detecting lane lines based on grayscale estimation and cascade Hough transform

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[0043] Using the method of the present invention, first use the C++ language to write lane detection software; then install the camera inside the front window of the car, calibrate various parameters of the camera, and collect the front image during the driving of the vehicle; The captured original image of the vehicle is input into the lane detection software as source data for processing; the experiment collects hundreds of source images under several driving conditions. When the driving is relatively stable, the success rate of the lane detection algorithm of the present invention is greater than 90 %, when the image is severely blurred due to violent bumps, the lane detection success rate can also reach more than 60%. For a higher resolution original image with a size of 656×491, the average processing time for each image is about 0.3s, and the operating environment is WinXP 2GHz, the compiler is Visual Studio 2005C++.

[0044] To sum up, the method of the present invention ma...

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Abstract

The invention provides a method for detecting lane lines based on grayscale estimation and cascade Hough transform, belonging to the technical field of image processing, and relating to image segmentation, image line geometrical characteristics detection and intelligent vehicle navigation simultaneously, which is mainly applicable to an auxiliary safety drive system. The method comprises the following steps: carrying out grayscale estimation on sensitive areas of an original image I of the collected vehicle road conditions ahead; dividing the sensitive areas into a vehicle shadow region, a roadway non-mark region and a roadway mark region (including the area of the car body of the vehicles ahead); adopting a mathematical morphology method to obtain a boundary image from the roadway mark region in the areas divided by the grayscale estimation; then carrying out Hough transform on the obtained boundary image of the roadway mark region to extract line image characteristics therein; and finally realizing the detection of the lane lines by searching end points of roadway mark boundary. Compared with the congeneric method, the method in the invention has stronger stability and wider application occasions and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to image segmentation and image linear geometric feature detection, and relates to intelligent vehicle navigation, and is mainly applicable to auxiliary safety driving systems in the field of intelligent transportation. Background technique [0002] Intelligent transportation system is a huge social system engineering, including auxiliary safety driving system, traffic management system, commercial vehicle operation system, electronic toll collection system, public transportation operation system, emergency management system, vehicle control system, etc. Among them, the assisted safety driving system is an important part of the system that has a relatively low cost and is closely related to the public, but has quite obvious social effects. It has huge social and economic development potential and can significantly improve the traffic safety level. Increase the mobility of traffic...

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Application Information

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IPC IPC(8): G01C21/26G01C21/34G06T7/00
Inventor 解梅刘叹
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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