Abstract
Aperiodic sinusoidal patterns that are cast by a GOBO (GOes Before Optics) projector are a powerful tool for optically measuring the surface topography of moving or deforming objects with very high speed and accuracy. We optimised the first experimental setup that we were able to measure inflating car airbags at frame rates of more than 50 kHz while achieving a 3D point standard deviation of ~500 µm. Here, we theoretically investigate the method of GOBO projection of aperiodic sinusoidal fringes. In a simulation-based performance analysis, we examine the parameters that influence the accuracy of the measurement result and identify an optimal pattern design that yields the highest measurement accuracy. We compare the results with those that were obtained via GOBO projection of phase-shifted sinusoidal fringes. Finally, we experimentally verify the theoretical findings. We show that the proposed technique has several advantages over conventional fringe projection techniques, as the easy-to-build and cost-effective GOBO projector can provide a high radiant flux, allows high frame rates, and can be used over a wide spectral range.
Highlights
1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Introduction Measuring the three-dimensional (3D) topography of macroscopic objects by using structured light requires (i) the projection of N ≥ 1 pattern(s) onto the object and (ii) the simultaneous recording of the pattern(s) that are modulated by the object topography
When measuring an object with a GOBO projection-based sensor, occlusions might restrict the surface area that is covered by both the projector and the cameras, which limits the maximum number of points that can be reconstructed
We considered three levels of noise that correspond to signalto-noise ratios of signal-to-noise ratios (SNRs) ≈ 19 dB, 17 dB, and 15 dB
Summary
Measuring the three-dimensional (3D) topography of macroscopic objects by using structured light requires (i) the (sequential) projection of N ≥ 1 pattern(s) onto the object and (ii) the simultaneous recording of the pattern(s) that are modulated by the object topography. Years of research and development have shown that the accuracy that can be achieved by such pattern projection systems depends directly on the number N of projected patterns[1,2,3]. Along with the increased demands on measurement accuracy, in recent years, requirements on measurement speed have risen, which necessitate high-speed pattern projection and recording and fast computation and evaluation. Well-known algorithms for determining 3D object coordinates by evaluating projected patterns are based on detecting two-dimensional (2D) point correspondences between two cameras or between one camera and the projector[4,5,6,7].
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