The traditional point pair features (PPF) algorithm lacks sufficient point cloud matching accuracy in precision industrial production and robustness to planar point clouds. To address these issues, this study proposes a novel point regions features (PRF) registration method. In this method, PRF point domain features enhance matching by incorporating the feature complexity and average direction of target point pairs within their respective neighborhoods as complementary features. The algorithm utilizes the complexity of different point domains as a weighted criterion for feature matching, conducting a weighted voting process. The point cloud is then obtained in the real working scene. Experimental results from common point cloud matching experiments in real-world scenarios show that the proposed PRF registration algorithm significantly improves point cloud accuracy and robustness with minimal impact on speed.