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Vehicle yaw angle determination method based on Hough transform

A method for determining the yaw angle, which is applied in the field of vehicle active safety systems, can solve the problems of difficult detection and easy wear of lane lines, and achieve the effects of strong anti-interference ability, reliable detection results, and high recognition accuracy

Active Publication Date: 2017-06-06
南方电网互联网服务有限公司
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Problems solved by technology

The lane position and shape of structured roads are mainly obtained by detecting lane markings and lane boundaries; however, in actual situations, lane lines on roads are easily worn out, making detection difficult, so special processing is required to accurately determine lane damage lane location

Method used

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  • Vehicle yaw angle determination method based on Hough transform
  • Vehicle yaw angle determination method based on Hough transform
  • Vehicle yaw angle determination method based on Hough transform

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Embodiment

[0028] Such as figure 1 Shown, the present invention is based on the vehicle yaw angle determination method of Hough transform, comprises the following steps:

[0029] S1: Continuously acquire images in front of the vehicle through the vehicle camera with a resolution of 640x 480 pixels.

[0030] S2: Capture each frame of image and cut out the part of the vehicle in front of the sky part, named Roil. Cutting out the sky part in the image can make the subsequent distance calculation more accurate, such as the calculation in step S7.

[0031] S3: Preprocessing Roil, which includes: converting the color image of Roil into a grayscale image, using the Sobel operator to obtain the first-order differential sobelx in the x direction and the first-order differential sobely in the y direction, and obtain the gradient and direction , converted to an 8-bit single-channel image for display.

[0032] S4: Binarize the 8-bit single-channel image converted in step S3 by using the global ad...

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Abstract

The invention discloses a vehicle yaw angle determination method based on Hough transform. The method comprises converting an image ahead of a vehicle into an 8-bit single-channel image, performing binaryzation by using a global adaptive threshold obtained by OTSU, and obtaining a straight line by using progressive probabilistic Hough transform; obtaining the length and the slope arc tangent value of a lane line to determine whether the lane line is a solid line or a dashed line; obtaining the distance of the solid line, and taking slide line with the smallest distance as a real lane solid line; obtaining a difference value between the dashed line slope arc tangent value and weighted average value thereof, and determining the dashed line with the least difference value as a real lane dashed line; finally, calculating, according to detected left and right lane lines, an intersection angle between the angular bisector of an intersection angle of the left and right lane lines and the axis Y of a coordinate system as the vehicle yaw angle. The vehicle yaw angle determination method is low in calculated amount, high in recognition accuracy and fast in recognition speed, and can quickly calculate the yaw angle of the vehicle, and can filter out various noises on the ground well.

Description

technical field [0001] The invention relates to the field of vehicle active safety systems, in particular to a method for determining a road line yaw angle. Background technique [0002] At present, lane detection is mainly used in the development of smart cars, and most of them are used in the visual navigation system or high lane warning system of smart cars. Due to the complexity of the road environment, most researches on lane detection technology are based on structured roads. Structured roads generally refer to expressways and some well-structured roads. The lane lines and road boundaries on these highways are clear, and the lane lines are generally continuous straight lines, curved lines or dashed lines. The lane position and shape of structured roads are mainly obtained by detecting lane markings and lane boundaries; however, in actual situations, lane lines on roads are easily worn out, making detection difficult, so special processing is required to accurately de...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/588
Inventor 朱静黄文恺汪程辉陈文达何俊峰江吉昌韩晓英吴羽伍冯洁
Owner 南方电网互联网服务有限公司
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