KEYWORDS: Structured light, Calibration, Image registration, 3D metrology, 3D modeling, 3D image processing, Optical spheres, Cameras, Clouds, Imaging systems
Automatic registration is a key researcher issue in 3D measurement field. In this work, we developed the
automatic registration system, which is composed of a stereo system with structured light and two axis
turntables. To realize the fully automatically 3D point registration, the novel method is proposed for
calibration the stereo system and the two turntable direction vector simultaneously. The plane calibration
rig with marked points was placed on the turntable and was captured by the left and right cameras of the
stereo system with different rotation angles of the two axis turntable. By the shot images, a stereo system
(intrinsically and extrinsically) was calibrated with classics camera model, and reconstruction 3D
coordinates of the marked points with different angle of the two turntable. The marked point in different
angle posted the specific circle, and the normal line of the circle around the turntable axis direction vector.
For the each turntable, different points have different circle and normal line, and the turntable axis
direction vector is calculated by averaging the different normal line. And the result show that, the
proposed registration system can precisely register point cloud under the different scanning angles. In
addition, there are no the ICP iterative procedures, and that make it can be used in registration of the
point cloud without the obvious features like sphere, cylinder comes and the other rotator.
The temporal phase unwrapping will become unstable, if fewer numbers of fringe patterns with different spatial
frequencies are used. In this paper, we present a modified phase unwrapping method based on the phase filtering, which
can be used to achieve correct phase-unwrapping with use of fewer numbers of fringe frequencies. An adaptive phase
filter is designed according to the phase-jumping characteristics to eliminate the phase noise. The window size of the
filter is adaptively determined according to the local noise levels. After filtering operation, we are able to obtain the
approximate phase value with filtering errors. In order to further eliminate the filtering residual errors, we take
unwrapping operation again to get the correct phase value. The simulation experimental results are also presented to
validate our proposed approach.
A phase reconstruction method using frequency-shifting is proposed. The frequency-shifting method is
developed based on the properties of trigonometric functions. The computer simulation and the
experimental result are also presented to demonstrate the feasibility and validity of the proposed
approach in phase reconstruction.
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