Monocular vision lane line detection method and distance measurement method thereof

Abstract

The invention discloses a monocular vision lane line detection method and a distance measurement method of the monocular vision lane line detection method and belongs to the field of vehicle driving safety auxiliary systems. The lane line detection method comprises the steps of shooting multiple frames of images when a vehicle is just started to obtain a reference lane line, then obtaining candidate real-time lane lines by every reading of a real-time image, performing region matching on the candidate real-time lane lines and the reference lane line, and if the region matching is successful, updating an inclination angle and outputting the reference lane line; if the region matching is failed and the failure emerges for the first time, recording the candidate real-time lane lines as temporary lane lines, if the failure emerges continuously and the reference lane line can be continuously successfully matched with the temporary lane lines, outputting the temporary lane lines. A distance between a body vehicle and a target vehicle can be calculated by setting a reference target on the basis of a projection relation between the reference target and the target vehicle in a vision collection system according to the lane line image detected by the method disclosed by the invention. The monocular vision lane line detection method and the distance measurement method of the monocular vision lane line detection method are suitable for vehicle lane line detection and distance measurement between two vehicles.

Description

technical field [0001] The invention belongs to the field of vehicle driving safety assistance systems, and in particular relates to a monocular vision lane line detection method and a vehicle ranging method based on the lane line detection method. Background technique [0002] At present, with the popularization of vehicles, vehicle collision avoidance and navigation have become popular research directions, and intelligent vehicle collision avoidance and navigation systems will be an important part of the future intelligent transportation system. [0003] Regardless of vehicle collision avoidance or navigation, fast and accurate recognition of lane lines is particularly important. At present, many vision-based lane line recognition detection methods have been proposed. Most of the methods first perform image segmentation and use straight lines for the segmented images. The detection method identifies lane markings. [0004] Accurate detection of lane lines is a necessary c...

AI Technical Summary

Problems solved by technology

[0006] Among them, the geometric similarity method needs to accurately measure the position and angle of the camera system or the visual acquisition system. If the position and angle measurement cannot reach a certain accuracy, the accuracy of the ranging result of the geometric similarity method will not be high; The geometric shape of the target has requirements, and distance measurement cannot be performed for all geometric shapes; the structured light method and the laser-assisted ranging method need laser as an auxiliary tool; the geometric optics method is divided into the aggregation method and the defocus method. Slow, accurate calibration of the defocus model in the defocus method is difficult

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