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BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors

1
Fraunhofer Institute for Applied Optics and Precision Engineering IOF, Albert-Einstein-Str. 7, 07745 Jena, Germany
2
Institute of Applied Physics, Abbe Center of Photonics, Friedrich Schiller University Jena, Albert-Einstein-Str. 15, 07745 Jena, Germany
3
Group for Quality Assurance and Industrial Image Processing, Department of Mechanical Engineering, Ilmenau University of Technology, Gustav-Kirchhoff-Platz 2, 98693 Ilmenau, Germany
*
Author to whom correspondence should be addressed.
This work is an extended version of our research published in 2019 at the conference “SPIE Dimensional Optical Metrology and Inspection for Practical Applications VIII” held in Baltimore, MD, USA, 16–17 April 2019.
Appl. Sci. 2019, 9(16), 3330; https://doi.org/10.3390/app9163330
Received: 14 June 2019 / Revised: 7 August 2019 / Accepted: 9 August 2019 / Published: 14 August 2019
(This article belongs to the Special Issue High-speed Optical 3D Shape and Deformation Measurement)
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Abstract

Pattern projection-based 3D measurement systems are widely used for contactless, non-destructive optical 3D shape measurements. In addition, many robot-operated automation tasks require real-time reconstruction of accurate 3D data. In previous works, we have demonstrated 3D scanning based on statistical pattern projection-aided stereo matching between two cameras. One major advantage of this technology is that the actually projected patterns do not have to be known a priori in the reconstruction software. This allows much simpler projector designs and enables high-speed projection. However, to find corresponding pixels between cameras, it is necessary to search the best match amongst all pixels within the geometrically possible image area (that is, within a range on the corresponding epipolar line). The well-established method for this search is to compare each candidate pixel by temporal normalized cross correlation of the brightness value sequences of both pixels. This is computationally expensive and interdicts fast real-time applications on inexpensive computer hardware. We show two variants of our algorithm “Binary Correspondence Search” (BICOS), which solve this task in significantly reduced calculation time. In practice, our algorithm is much faster than traditional, purely cross-correlation-based search while maintaining a similar level of accuracy. View Full-Text
Keywords: real-time; active stereo vision; 3D measurement; GOBO projection; statistical pattern projection; aperiodic sinusoidal fringes; GPGPU; BICOS; correspondence search; binary features real-time; active stereo vision; 3D measurement; GOBO projection; statistical pattern projection; aperiodic sinusoidal fringes; GPGPU; BICOS; correspondence search; binary features
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Dietrich, P.; Heist, S.; Landmann, M.; Kühmstedt, P.; Notni, G. BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors. Appl. Sci. 2019, 9, 3330.

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