Measured data are obtained through a laser scanner in reverse engineering. The real data inevitably contain unreasonably noise error during measuring. The noise error causes the reconstructed curve and surface rough. Therefore it is essential to remove the noise error. This paper investigates the method on reducing noise error of the measured data obtained through laser line scanning. The method on reducing noise error is closely related to the organization of the point cloud data. This paper analyzes the mathematical model about the point cloud data error. The noise error is mainly caused by random error. The characteristic of noise error is that the swing value is bigger and the peak arises on the scanning line. According to this feature

a method named the random filter algorithm is put forward for reducing noise error

and it is simple

quick and practical. The procedure of this algorithm is first to compare the relative position among the successive points. Then the points that their positions oscillate bigger are judged noise error according to a threshold and will be removed. The principle and the step are described in detail

and it is proved by some examples that the processing result of the method is effective and can meet the requirements of curve and surface reconstruction.