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Research of using Kalman filter to do specific information track in video image sequences is a hot topic in the tracking direction currently. But most researches processed the noise of Kalman filter by assigning a specific value in the initial step. By constantly tuning the parameters the algorithm can achieve better tracking results. However, working in this way not only did not follow the rules of the original data, but also adjusting parameters is a time-consuming job. For this reason, the paper proposes a Kalman filter process noise and measurement noise assignment algorithm which is used in lane detection. By processing part of the offline data, the algorithm can estimate the basic parameters of the noise. Use lane tracking to validate the algorithm in this article and experiments show that the proposed methods achieve good detection results while the time of processing each frame is about 50 ms which meet the real-time requirements.