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Assessment of High Speed Imaging Systems for 2D and 3D Deformation Measurements: Methodology Development and Validation

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Abstract

Ultra high-speed and moderate speed image acquisition platforms have been characterized, with special emphasis on the variability and accuracy of the measurements obtained when employed in either 2D or 3D computer vision systems for deformation and shape measurements. Specifically, the type of image distortions present in both single channel cameras (HS-CMOS) and multi-channel image intensified cameras (UHS-ICCD) are quantified as part of the overall study, and their effect on the accuracy of experimental measurements obtained using digital image correlation have been determined. Results indicate that established methods for noise suppression and recently developed models for distortion correction can be used effectively in situations where the primary intensity noise components are characterized by minimal cross-talk and stationary spatial distortions. Baseline uniaxial tension experiments demonstrate that image correlation measurements using high speed imaging systems are unbiased and consistent with independent deformation measurements over the same length scale, with point-to-point strain variations that are similar to results obtained from translation experiments. In this study, the point-to-point variability in strain using the image intensified system is on the order of 0.001, whereas the non-intensified system had variability of 0.0001. Results confirm that high speed imaging systems can be utilized for full field two and three-dimensional measurements using digital image correlation methods.

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Notes

  1. The UHS-ICCD imaging system used in this study is the Imacon 200 manufactured by DRS Hadland.

  2. The HS-CMOS imaging system used in this study is the Phantom V7.1 manufactured by Vision Research, Inc.

  3. The figure provides qualitative information regarding the arrangement of optical and digitization elements within the UHS-ICCD image acquisition system. The actual shape of a component, the number of components, their orientation and spatial relationship relative to other components should not be inferred from the schematic drawing.

  4. The same randomly selected locations are used in all eight channels.

  5. Saturation is known to occur for all points with I ≥ 1,023 since no additional range is possible. In this case, the standard deviation is zero.

  6. Several approaches, including image averaging, domain filtering and homomorphic masking, are developed. When used to correct selected UHS-ICCD images, the results are not encouraging; increases in noise level are observed in some cases and the methods are not pursued further in this study.

  7. The flat field correction process employed in this study is performed external to the IMACON software using algorithms developed by Correlated Solutions, Incorporated.

  8. Additional experiments are performed with gain values of 1 and 2, with similar results, indicating that changes in initial conditions for the micro-channel plates did not appreciably alter local variability in the intensity response.

  9. All 2D image correlation studies are performed using a modified version of VIC-2D, Correlated Solutions, Inc http://www.correlatedsolutions.com.

  10. Lower spatial resolution in the UHS-ICCD system mandated a larger subset size to have sufficient contrast for accurate image correlation.

  11. Translation tests performed using shifted copies of the reference image gave correct translation results, confirming that the image correlation algorithms are performing adequately.

  12. The CMOS sensor has 8 bit quantization. The 8 bit data is scaled to 10 bits for comparison to UHS-ICCD results using the formula \( I_{{{\text{10}}\,\,{\text{bits}}}} = 1024\,{\left( {{I_{{{\text{8}}\,\,{\text{bits}}\,}} } \mathord{\left/ {\vphantom {{I_{{{\text{8}}\,\,{\text{bits}}\,}} } {256}}} \right. \kern-\nulldelimiterspace} {256}} \right)} \), where I8 bits > 16 to minimize effect of dark field differences between systems on the computed variations.

  13. ICCD data is obtained from Fig. 4 and limited to same range as obtained from the CMOS sensor for comparative purposes.

  14. Flat-field corrections performed on the Phantom V7.1 images did not decrease scatter in the measured intensity field data.

  15. Flat field corrected images are used to obtain displacement fields. The results are nearly identical to the results shown in Fig. 10(a), and hence are not reported separately.

  16. Even though the spatial distortion function does correct for stationary fields, applying the UHS-ICCD distortion fields did not improve the results obtained using flat field correction and shown in Fig. 7. The lack of improvement further demonstrates that image-to-image variability in the pixel intensity values is the primary source of errors in the UHS-ICCD imaging systems.

  17. The width of the correction region is directly related to the subset size used for the displacement measurements.

  18. Dead pixels must be removed from the digital image correlation process to eliminate this effect. Highly non-linear response is generally a function of the incident light intensity and hence is not a stationary, spatially varying distortion effect that can be corrected.

  19. For the same set of experiments, the UHS-ICCD system is unbiased when estimating the whole-field response, with errors in average strain less than 100 micro strain.

  20. Any significant mismatch between initializing the image acquisition processes in the stereo cameras can result in unacceptable errors in the measurements. When using two UHS-ICCD cameras in a 3D configuration, oscilloscope measurements confirmed that the time delay between trigger pulse for both the cameras is on the order of a few picoseconds, with a maximum difference in camera initialization on the order of ±2.5 ns. For the HS-CMOS systems, the time delay is less than 1 μs. Such small time delays are insignificant for the experiments performed in this study.

  21. Stereo calibration and 3D image correlation are performed using software developed by Correlated Solutions, Incorporated, http://www.correlatedsolutions.com.

  22. Results from a series of dynamic events will be reported in a future publication.

  23. Image sensors integrate the light intensity emanating from points on an object over the specified exposure time.

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Acknowledgements

The technical support of Dr. Bruce Lamattina and the financial assistance provided through the Army Research Office grant DAAD19-02-1-0343 and the assistance provided by Dr. A. Rajendren and Dr. M. Zikry and the support provided through DURIP grant DAAD19-01-1-0391 are gratefully acknowledged. Finally, the financial support provided by the University of South Carolina College of Engineering and Information Technology in support of the DURIP award is acknowledged.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of South Carolina, 300 South Main Street, Columbia, SC, 29208, USA

    V. Tiwari, M. A. Sutton & S. R. McNeill (SEM member)

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  1. V. Tiwari
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  2. M. A. Sutton
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  3. S. R. McNeill
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Correspondence to M. A. Sutton.

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Tiwari, V., Sutton, M.A. & McNeill, S.R. Assessment of High Speed Imaging Systems for 2D and 3D Deformation Measurements: Methodology Development and Validation. Exp Mech 47, 561–579 (2007). https://doi.org/10.1007/s11340-006-9011-y

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