In industrial measurements and online monitoring, full-field and high-efficiency deformation analysis has been increasingly important and highly demanded in recent years. In this paper, a fast three-dimensional digital image correlation (3D-DIC) method was proposed to implement real-time measurement. Two improvements were suggested to accelerate the computation speed without sacrificing the accuracy. First, an efficient inverse compositional Gauss–Newton (IC-GN) algorithm was developed to avoid redundant computation. Moreover, a seed point-based parallel method was extended for 3D-DIC to achieve parallel computation and faster convergence speed. The detailed process of the real-time measurement using the proposed method was also introduced. Benefiting from the efficient IC-GN algorithm and parallel processing software we developed, full-field, real-time 3D deformation monitoring was realized at a frame rate of 10 frames/s with resolution of 5000 points per frame. For validation, the displacement field of a four-point bending beam was determined by the real-time 3D-DIC. As an application, the real-time human pulse diagnosis was also performed based on the presented technique. Experimental results verify that the proposed real-time 3D-DIC is practicable and effective for traditional Chinese medicine.

The technique of digital image correlation (DIC), which has been widely used for noncontact deformation measurements in both the scientific and engineering fields, is greatly affected by the quality of speckle patterns in terms of its performance. This study was concerned with the optimization of the digital speckle pattern (DSP) for DIC in consideration of both the accuracy and efficiency. The root-mean-square error of the inverse compositional Gauss–Newton algorithm and the average number of iterations were used as quality metrics. Moreover, the influence of subset sizes and the noise level of images, which are the basic parameters in the quality assessment formulations, were also considered. The simulated binary speckle patterns were first compared with the Gaussian speckle patterns and captured DSPs. Both the single-radius and multi-radius DSPs were optimized. Experimental tests and analyses were conducted to obtain the optimized and recommended DSP. The vector diagram of the optimized speckle pattern was also uploaded as reference.

The development of stereo-digital image correlation (stereo-DIC) enables the application of vision-based technique that uses digital cameras to the deformation measurement of materials and structures. Compared with traditional contact measurements, the stereo-DIC technique allows for non-contact measurement, has a non-intrusive characteristic, and can obtain full-field deformation information. In this paper, a speckle-based calibration method is developed to calibrate the stereo-DIC system when the system is applied for deformation measurement of large engineering components. By combining speckle analysis with the classical relative orientation algorithm, relative rotation and translation between cameras can be calibrated based on analysis of experimental speckle images. For validation, the strain fields of a four-point bending beam and an axially loaded concrete column were determined by the proposed calibration method and stereovision measurement. As a practical application, the proposed calibration method was applied for strain measurement of a ductile iron cylindrical vessel in the drop test. The measured results verify that the proposed calibration method is effective for deformation measurement of large engineering components.

The accuracy of strain measurement using a common optical extensometer with two-dimensional (2D) digital image correlation (DIC) is not sufficient for experimental applications due to the effect of out-of-plane motion. Although three-dimensional (3D) DIC can measure all three components of displacement without introducing in-plane displacement errors, 3D-DIC requires the stringent synchronization between two digital cameras and requires complicated system calibration of binocular stereovision, which makes the measurement rather inconvenient. To solve the problems described above, this paper proposes a self-calibration single-lens 3D video extensometer for non-contact, non-destructive and high-accuracy strain measurement. In the established video extensometer, a single-lens 3D imaging system with a prism and two mirrors is constructed to acquire stereo images of the test sample surface, so the problems of synchronization and out-of-plane displacement can be solved easily. Moreover, a speckle-based self-calibration method which calibrates the single-lens stereo system using the reference speckle image of the specimen instead of the calibration targets is proposed, which will make the system more convenient to be used without complicated calibration. Furthermore, an efficient and robust inverse compositional Gauss-Newton algorithm combined with a robust stereo matching stage is employed to achieve high-accuracy and real-time subset-based stereo matching. Tensile tests of an Al-alloy specimen were performed to demonstrate the feasibility and effectiveness of the proposed self-calibration single-lens 3D video extensometer.

In this paper, an extrinsic calibration method for a non-overlapping camera network is presented based on close-range photogrammetry. The method does not require calibration targets or the cameras to be moved. The visual sensors are relatively motionless and do not see the same area at the same time. The proposed method combines the multiple cameras using some arbitrarily distributed encoded targets. The calibration procedure consists of three steps: reconstructing the three-dimensional (3D) coordinates of the encoded targets using a hand-held digital camera, performing the intrinsic calibration of the camera network, and calibrating the extrinsic parameters of each camera with only one image. A series of experiments, including 3D reconstruction, rotation, and translation, are employed to validate the proposed approach. The results show that the relative error for the 3D reconstruction is smaller than 0.003%, the relative errors of both rotation and translation are less than 0.066%, and the re-projection error is only 0.09 pixels.

To reduce the uncertainty region of a three-dimensional (3D) position, a four-camera 3D digital image correlation (3D-DIC) system was built by orthogonally arranging two sets of two-camera DIC systems. The theoretical model proposed herein revealed the relationship between 3D coordinates and system parameters and the propagation of the matching error to the position error. Numerical simulation and experiment were conducted to verify the theory. The simulation and experimental results indicated that the 3D position error of the four-camera system was smaller than that of the two-camera DIC system. The present contribution proves the feasibility of using four-camera DIC systems to improve measurement accuracy.