Incremental point clouds registration is studied in this paper. A rapid method for point clouds registration based on reference points is proposed, which consists of the coarse registration and fine registration. Firstly, a set of reference points is applied as an assistant utility to measure the object. The transformation parameters are estimated by using the reference points only for coarse registration, and then dense point clouds data will be transformed to the same coordinate system. Secondly, taking the coarse registration results as the initial value, the improved Interactive Closest Point (ICP) algorithm is used in fine registration the original corresponding points are established rapidly by using the k-d tree searching algorithm. Finally, Preview Model Parameters Evaluation Random Sample Consensus (PERANSAC) algorithm is utilized to remove outliers. The experimental result shows that this method in finding original corresponding points can greatly improve the computation efficiency and also improve the registration accuracy.