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In order to reduce the false positive rate of the lane recognition algorithm in different road circumstances such as the lane is prone to the occlusion of shadow and the pavements appear blanched. A lane detection algorithm based on improved SIS threshold algorithm and line segment detection (LSD) is proposed. First of all, the improved SIS threshold algorithm is used to transform the image data into binary data, during the image preprocessing stage. Then the line segment detection (LSD) algorithm is applied to detect whether there exists straight line in the image. Moreover, the parallel lines are used to estimate the position of the vanishing point, which in turn eliminate the interference. Finally, the location of the lane line is determined in the lane line region of interest accurately through the analysis of the continuity of lane line and the values of lane spacing. The method is verified by using California institute of technology"s driveway data set and the actual city road and video of the highway. The results show that the algorithm has low false positive rate and high robustness. Moreover, the lane line can be identified precisely and quickly in the complex environment.