Projected feature assisted coarse to fine point cloud registration method for large-size 3D measurement

Abstract

Fringe projection profilometry has gained significant interest due to its high precision, enhanced resolution, and simplified design. Typically, the spatial and perspective measurement capability is restricted by the lenses of the camera and projector in accordance with the principles of geometric optics. Therefore, large-size object measurement requires data acquisition from multiple perspectives, followed by point cloud splicing. Current point cloud registration methods usually rely on 2D feature textures, 3D structural elements, or supplementary tools, which will increase costs or limit the scope of the application. To address large-size 3D measurement more efficiently, we propose a low-cost and feasible method that combines active projection textures, color channel multiplexing, image feature matching and coarse-to-fine point registration strategies. Using a composite structured light with red speckle patterns for larger areas and blue sinusoidal fringe patterns for smaller ones, projected onto the surface, which allows us to accomplish simultaneous 3D reconstruction and point cloud registration. Experimental results demonstrate that the proposed method is effective for the 3D measurement of large-size and weak-textured objects.