The surface quality affected by the morphology has significant effect on the mechanical properties of laser additive manufactured parts. To ensure the high service properties of forming parts, the surface morphology is needed to be inspected. In this paper, a rapid inspection method of surface morphology for laser additive manufactured parts is proposed based on 3D computer vision. Compared to the conventional inspection methods, the expensive instruments and complex operating procedures are reduced to achieve the inspection rapidly. During the inspection process, the 3D point cloud of laser additive manufactured part’s surface is acquired by a laser scanner. The VoxelGrid algorithm is selected to conduct the down-sampling to reduce the number of points and improve uniformity of the 3D point cloud. The obtained down-sampled 3D point cloud is filtered by radius outlier removal filter algorithm to eliminate noise points and segmented by random sample consensus algorithm to remove the substrate region in 3D point cloud. The surface morphologies are reconstructed by the ball pivoting, alpha shaping and poisson surface reconstruction algorithms. The accuracies of reconstructed surface from different algorithms are compared and the surface morphology with the highest accuracy is used to evaluate quantitatively the surface quality of part. The results show that the proposed method can obtain rapidly and exactly the surface morphology and quality.