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This paper presents an automatic power line extraction method based on LIDAR data in forest. The method is based on statistical analysis and binary image processing technology. First, the height threshold is used to separate the power line candidate data, and a set of criteria (for example, height criteria, density criteria and histogram threshold) are used to statistically analyze the candidate set and select the candidate point of the power line. Then the candidate points are transformed into binary image, and the morphological optimization is carried out. The image segmentation is carried out by using the probability-based Hough linear transformation. Finally, the segmentation of the power line image were transformed into a 3D points cloud, and the power line point cloud was refined by using region growth. Experiments were carried out using 4 sets of LiDAR data in different forest environments. The results show that the proposed algorithm can extract the power line completely in the forest environment, and the power line classification accuracy is higher, which has higher utilization value for the power line inspection.