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

Area of Science:

• Optics and Photonics
• Computer Vision
• Metrology

Background:

• Fringe projection profilometry offers high precision but is limited in measuring large objects due to geometric optics constraints.
• Existing point cloud registration methods for large objects often require multiple perspectives, supplementary tools, or rely on 2D/3D features, increasing cost and complexity.

Purpose of the Study:

• To develop an efficient, low-cost method for large-size 3D measurement and point cloud registration.
• To overcome the limitations of traditional fringe projection profilometry for large and weakly textured objects.

Main Methods:

• A composite structured light approach using red speckle and blue sinusoidal fringe patterns projected simultaneously.
• Integration of active projection textures, color channel multiplexing, image feature matching, and coarse-to-fine point registration strategies.

Main Results:

• Simultaneous 3D reconstruction and point cloud registration were achieved using the proposed composite structured light.
• The method demonstrated effectiveness in the 3D measurement of large-size and weak-textured objects.

Conclusions:

• The proposed method provides a feasible and cost-effective solution for large-scale 3D metrology.
• This technique enhances the applicability of fringe projection profilometry to a broader range of objects and applications.