ing at the difficulty of extracting the key contour features of printed circuit boards, an algorithm for transforming the folded edge into the boundary and extracting the key contour feature points is proposed. First, the algorithm establishes a topological structure of the original point cloud data of the printed circuit board by using k dimensional-tree, and realize fast search of the closest k neighborhood points. Pass-through filtering algorithm is used to complete the pre-processing of the printed circuit board point cloud. Second, Random Sample Consensus algorithm is used to extract the plane features with the largest area in the printed circuit board separately, so that the key contour features are spatially separated. The point clustering of the fold edge feature is completed by Euclidean clustering based on normal angle and realize the idea of transforming the folded edge into the boundary. Finally, according to the relationship between set threshold and vector angle between k neighborhood points, one can determine whether the query point belongs to the boundary contour feature point. Experimental results show that the proposed algorithm can extract the key contour feature line of printed circuit board point cloud more completely.