Multi-lane line tracking method based on Kalman filter bank

Abstract

The invention discloses a multi-lane line tracking method based on a Kalman filer bank, which belongs to the technical field of processing of digital images. The method comprises the following steps of: outputting the optimal estimation value of a lane line by using a Kalman filter model on the basis of performing lane line detection on an acquired vehicle front road image by establishing the Kalman filter model tracked by the lane line; and when the same lane line is detected through continuous 25 road images, determining that the optimal estimation of a Kalman filter is effective, and using the optimal estimation value output by the Kalman filter as a detection result. By the method, the detection result of the lane line in a lane departure warning system is more stable, so that the phenomena of inaccurate lane line detection or detection omission caused by vehicle body vibration, illumination variation, road surface damages and the like are greatly reduced; and according to set quantity of filters, a corresponding lane line number can be tracked simultaneously, a region of interest (ROI) of the lane line can be relatively unitarily tracked, and the detection accuracy and the disturbance resistance of the lane line are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and mainly relates to a method for simultaneously tracking multiple lane lines detected in road video images. Background technique [0002] Lane Departure Warning System (Lane Departure Warning System, LDWS) is a system that assists drivers to reduce traffic accidents caused by lane departure by means of an alarm. The continuous progress of social economy and the rapid development of modern computer technology, the integration of new technologies such as multi-sensor technology and communication control theory, make the popularization and application of LDWS possible, thereby maximizing the safety of driving and reducing social and economic losses. reduced to a minimum. [0003] At present, the implementation of LDWS is based on the method of computer vision. First, the lane line is recognized in the collected road video images, and then it is judged whether to issue a departure...

AI Technical Summary

Problems solved by technology

According to the lane lines that have been detected, define a small area that only contains a part of a lane line, and input the coordinates of this small area as sample information into the Kalman filter to predict the next small area that contains this lane line. This method is for 1 The improvement of the method narrows the area of ​​interest from including all lanes to only a certain part of a lane, which improves the detection accuracy of lanes, but still cannot completely avoid the problem that LDWS cannot detect lanes normally. This method is detailed See literature: Yu Houyun, Zhang Weigong. Lane Line Recognition and Tracking Based on Dynamic Region of Interest. Industrial Instrumentation and Automation Devices. Issue 5, 2009.

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