Camera calibration is crucial for geometric vision-based three-dimensional (3D) deformation measurement tasks. Among existing calibration techniques, the one based on planar targets has attracted much attention in the community due to its flexibility and reliability. Our study proposes a calibration technique to obtain high-accuracy internal and external parameters based on low-cost ordinary planar patterns. The proposed method determines the optimal internal parameters for each camera by refining 3D coordinates of planar control points, where an analytic model of optics distortion is presented to enable lens distortion to be corrected directly in subsequent external calibration and underlying 3D reconstruction. External parameters are estimated by minimizing a bundle adjustment framework, which is carefully designed based on the proposed distortion correction model and depth parameterization. In contrast to the existing techniques, the proposed method is capable of obtaining a high-accuracy calibration with ordinary targets rather than the well-designed and fabricated ones. We experimented the proposed method with a calibration performance analysis and a displacement measurement; both results demonstrated the accuracy and robustness.
Measuring surface deformation of objects with natural patterns using digital image correlation (DIC) is difficult due to the challenges of the pattern quality and discriminative pattern matching. Existing studies in DIC predominantly focus on the artificial speckle patterns while seldom paying attention to the inevitable natural texture patterns. We propose a recursive-iterative method based on salient features to measure the deformation of objects with natural patterns. The method is proposed to select salient features according to the local intensity gradient and then to compute their displacements by incorporating the inverse compositional Gauss–Newton (IC-GN) algorithm into the classic image pyramidal computation. Compared with the existing IC-GN-based DIC technology, the use of discriminative subsets allows avoidance of displacement computation at pixels with poor spatial gradient distribution. Furthermore, the recursive computation based on the image pyramid can estimate the displacements of the features without the need for initial value estimation. This method remains effective even for large displacement measurements. The results of simulation and experiment prove the method’s feasibility, demonstrating that the method is effective in deformation measurement based on natural texture patterns.
Monitoring the static and dynamic displacements of large engineering structures, such as buildings and bridges, can provide quantitative information for evaluating structural safety and maintenance purposes. Camera calibration is a key process in vision-based sensor systems for remote displacement measurement. Due to the large field of view of engineering structures, conventional camera calibration methods using precise calibration boards are difficult to apply. A modified calibration method for a binocular stereo vision system based on the epipolar constraint relationship is proposed to simplify the calibration process. Due to the absence of reference points in outdoor applications, an unmanned aerial vehicle that carries a reference marker is adopted. During its flight in the field, sequential images are captured simultaneously with the left and right imaging stations. An alternative to determine the scale factor is also proposed, which provides adequate precision for camera calibration. Two important issues are discussed, including the number of reference points and their selection with regards to the depth of view. The experimental results show that the proposed method is convenient to apply in outdoor situations and can achieve high accuracy in displacement measurement.
Digital image correlation is an effective way for accurate dimensional measurements with merits of non-contact and high precision abilities. Accurate calibration for the binocular stereo vision system is critical. A simple calibration method has been proposed in this study with the use of an inertial measurement unit (IMU) on each imaging station. As the IMU is aligned with the optical axis of the camera, the orientation of the camera is known. This helps in determining the rotation matrix of the extrinsic parameter of the camera based on the epipolar constraint relationship. The experimental results show that the proposed method has good accuracy and flexibility
Infrared Thermography is a non-contact technique for non-destructive evaluations that has been widely used for inspection of structural materials. The prediction of defect depth is the most obvious advantage compared with other non-destructive techniques. Several thermal signal processing technologies and quantitative measurement methods have been reported in literature. However, most of those methods are only applicable to Pulse Infrared Thermography and Lock-In Thermography. In this paper, Phase Fourier Analysis (PFA) was used to determine the defect location and Logarithm Second Derivative Time (LSDT) was used to calculate the defect depth with Long Pulse Thermography (LPT). The experimental results were compared with numerical simulations of a Glass Fiber Reinforced Plastics (GFRP) panel with predesigned defects. It is found that the thermal signal processing can enhance the defect contrast and the specific characterize time in LSDT has a linear relationship with the square of depth.
Digital image correlation (DIC) has been successfully applied for evaluating the mechanical behavior of biological tissues. A three-dimensional (3-D) DIC system has been developed and applied to examining the motion of bones in the human foot. To achieve accurate, real-time displacement measurements, an algorithm including matching between sequential images and image pairs has been developed. The system was used to monitor the movement of markers which were attached to a precisely motorized stage. The accuracy of the proposed technique for in-plane and out-of-plane measurements was found to be −0.25% and 1.17%, respectively. Two biomedical applications were presented. In the experiment involving the foot arch, a human cadaver lower leg and foot specimen were subjected to vertical compressive loads up to 700 N at a rate of 10 N/s and the 3-D motions of bones in the foot were monitored in real time. In the experiment involving distal tibio fibular syndesmosis, a human cadaver lower leg and foot specimen were subjected to a monotonic rotational torque up to 5 Nm at a speed of 5 deg per min and the relative displacements of the tibia and fibula were monitored in real time. Results showed that the system could reach a frequency of up to 16 Hz with 6 points measured simultaneously. This technique sheds new lights on measuring 3-D motion of bones in biomechanical studies.
Proc. SPIE. 8769, International Conference on Optics in Precision Engineering and Nanotechnology (icOPEN2013)
KEYWORDS: Detection and tracking algorithms, Imaging systems, Speckle, Cameras, Error analysis, High speed cameras, 3D metrology, Wind turbine technology, Digital image correlation, 3D image processing
The measurement of the rotating object is of great significance in engineering applications. In this study, a high-speed
dual camera system based on 3D digital image correlation has been developed in order to monitor the rotation status of
the wind turbine blades. The system allows sequential images acquired at a rate of 500 frames per second (fps). An
improved Newton-Raphson algorithm has been proposed which enables detection movement including large rotation and
translation in subpixel precision. The simulation experiments showed that this algorithm is robust to identify the
movement if the rotation angle is less than 16 degrees between the adjacent images. The subpixel precision is equivalent
to the normal NR algorithm, i.e.0.01 pixels in displacement. As a laboratory research, the high speed camera system was
used to measure the movement of the wind turbine model which was driven by an electric fan. In the experiment, the
image acquisition rate was set at 387 fps and the cameras were calibrated according to Zhang’s method. The blade was coated with randomly distributed speckles and 7 locations in the blade along the radial direction were selected. The displacement components of these 7 locations were measured with the proposed method. Conclusion is drawn that the
proposed DIC algorithm is suitable for large rotation detection, and the high-speed dual camera system is a promising, economic method in health diagnose of wind turbine blades.
We conduct displacement/strain measurements on the microscale using light microscopy and digital image correlation (DIC). Errors in the measurements attributed to the optical arrangement and aberration induced at high magnification are identified using a warping function. Coefficients of the warping function are determined using a simple technique that employs a precisely made orthogonal cross-grating plate. By acquiring images of the grating and identifying the nodes using subpixel techniques, a relationship between the object and the image planes is established. Thus, the displacement/strain derived by means of DIC is corrected by converting the displacement components in the image plane to the coordinate system existing on the object's surface. The approach is validated through a determination of the elastic properties of common metals; errors in estimation of the elastic modulus were within 4%. Although surface preparation generally plays a critical role in successful application of DIC, it is found to be of minimal importance under high magnification. Instead, the natural surface texture can be used with adjustment of the light incident angle. Results of the study show that DIC is a powerful tool in performing displacement/strain measurements on the microscale using a light microscope provided that an adequate correction is employed for image distortion.
Optical methods are becoming commonplace in investigations of the physical and mechanical behavior of biological tissues. Digital image correlation (DIC) is a versatile optical method that shows tremendous promise for applications involving biological tissues and biomaterials. We present the fundamentals of DIC with an emphasis on the application to biological materials. An approach for surface preparation is described that facilitates its application to hydrated substrates. Three examples are presented that highlight the use of DIC for biomedical research. The first example describes the use of DIC to study the mechanical behavior of arterial tissues up to 40% elongation. The second example describes an evaluation of the mechanical properties of bovine hoof horn in the dehydrated and fully hydrated states. Uniaxial tension experiments are performed to determine the elastic modulus (E) and Poisson's ratio () of both the arterial and dermal tissues. Spatial variations in the mechanical properties are evident from the full-field characterization of both tissues. Finally, an application of DIC to study the evolution of loosening in cemented total hip replacements is described. The noncontact analysis enables measurement of the relative displacement between the bone/bone cement and bone cement/prosthesis interfaces. Based on the elementary optical arrangement, the simple surface preparation, and the ability to acquire displacement/strain measurements over a large range of deformation, DIC should serve as a valuable tool for biomedical research. Further developments will enable the use of DIC for in vivo applications.