Lane line identification method and lane line identification system

Abstract

The invention provides a lane line identification method and a lane line identification system. The lane line identification method comprises steps that an interested area is delineated in an acquired gray level image comprising a lane line; a matched filter is used for multidimensional matching filtering; the top hat transformation of the interested area of the image after the multidimensional matching filtering is carried out; by comparing a preset gray level adaptive threshold with a to-be-detected pixel point, a lane line characteristic point is screened out; the back projection transformation of the lane line characteristic is carried out to acquire a two-dimensional raster map; the neighborhood clustering processing of the two-dimensional raster map is carried out, and the curve fitting of the lane line pixel point is carried out, and then the lane line of the lane, on which a vehicle drives, is determined by combining with the current position of the vehicle. The characteristic enhancement of the lane line area in various environments is realized, and influences of changes of external conditions on the lane line identification based on machine vision are greatly reduced, and the accuracy of the subsequent lane line identification is improved.

Description

technical field [0001] The invention relates to the field of automobile auxiliary driving, in particular to a lane line recognition method and system. Background technique [0002] With the increase of car ownership, road traffic accidents have become a serious problem facing the world. Therefore, in the field of intelligent transportation systems, the development of intelligent vehicles has received widespread attention. Using computer vision for autonomous driving and assisted navigation is the current mainstream Research direction, the detection and tracking of lane lines is a core technology for the development of driver assistance systems and unmanned driving. For lane line recognition, many scholars have carried out extensive research. In general, machine vision-based lane recognition technology mainly includes three steps: lane feature point extraction, lane boundary fitting and lane tracking technology. [0003] The extraction of lane line feature points usually ad...

AI Technical Summary

Problems solved by technology

In addition, the linear-parabolic model is also widely used in the lane line model, but this method generally assumes that at the initial detection moment, the lane line is straight, the vehicle is parallel to the lane line, and there are no other objects in the image field of view except the lane boundary. The linear object boundary, etc., which limits the scope of application of the model algorithm

[0005] To sum up, under the existing technical conditions, the recognition of lane lines is easily affected by external factors, the recognition effect is not good, and the accuracy rate is not high

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