Non-contact 3D laser imaging technology is used to accurately detect 3D printing surface forming defects, and an automatic detection method of 3D printing surface forming defects based on 3D laser imaging technology is proposed. 3D laser point cloud data of 3D printed surface forming materials were obtained by using the scanner of 3D laser imaging system with vertical incidence scanning. The sample consistency initial registration algorithm is selected to carry out the coarse registration of laser point cloud. The accurate registration of laser point cloud is achieved by removing outliers and minimizing errors by using point-to-surface ICP algorithm. Using the four-quadrant near point search algorithm, linear interpolation is used to process the near 3D projection points of the defect pixels, and the 3D coordinate values of the defect points of 3D printing surface molding are obtained. The experimental results show that the method can effectively detect different types of defects such as holes and printing dislocation of 3D printing surface forming materials, and obtain accurate defect location results.