Motion measurements of explosive shock waves based on an event camera.

Shock wave measurement is vital in assessing explosive power and designing warheads. To obtain satisfactory observation data of explosive shock waves, it is preferable for optical sensors to possess high-dynamic range and high-time resolution capabilities. In this paper, the event camera is first employed to observe explosive shock waves, leveraging its high dynamic range and low latency. A comprehensive procedure is devised to measure the motion parameters of shock waves accurately. Firstly, the plane lines-based calibration method is proposed to compute the calibration parameters of the event camera, which utilizes the edge-sensitive characteristic of the event camera. Then, the fitted ellipse parameters of the shock wave are estimated based on the concise event data, which are gained by utilizing the characteristics of the event triggering and shock waves' morphology. Finally, the geometric relationship between the ellipse parameters and the radius of the shock wave is derived, and the motion parameters of the shock wave are estimated. To verify the performance of our method, we compare our measurement results in the TNT explosion test with the pressure sensor results and empirical formula prediction. The relative measurement error compared to pressure sensors is the lowest at 0.33% and the highest at 7.58%. The experimental results verify the rationality and effectiveness of our methods.

Interferometric-scale full-field vibration measurement by a combination of digital image correlation and laser vibrometer.

Digital Image Correlation (DIC) is a crucial noncontact full-field optical measurement method used in various fields. However, in practical applications, DIC is affected by systematic and random noises, leading to experimental resolutions lower than theoretical ones. In this study, we proposed a laser Doppler vibrometer guided DIC to perform vibration measurements. 3D-DIC obtains a sequence of out of displacement field initially. A three-dimensional frequency domain collaborative filtering (3D-FDCF) method that utilizes Laser Doppler vibrometer (LDV) single-point data to assist in processing of the displacement field sequence pixel-wise is adopted. The 3D-FDCF method combines lowpass filtering in the spatial frequency domain with LDV-guided bandpass filtering in the temporal frequency domain. The effectiveness of the 3D-FDCF method is demonstrated through a comparison among DIC data, the filtered DIC data, and continuously scanning LDV data. The experiment results demonstrate the 3D-FDCF method's capability in measuring vibration amplitudes of several hundred nanometers with the size of a test sample of about 100 mm × 100 mm, supporting the statement of interferometric scale full-field vibration measurement by DIC with the guidance of the LDV data.

Image-registration-based solar meridian detection for accurate and robust polarization navigation.

Skylight polarization, inspired by the foraging behavior of insects, has been widely used for navigation for various platforms, such as robots, unmanned aerial vehicles, and others, owing to its stability and non-error-accumulation. Among the characteristics of skylight-polarized patterns, the angle of polarization (AOP) and the degree of polarization (DOP) are two of the most significant characteristics that provide abundant information regarding the position of the sun. In this study, we propose an accurate method for detecting the solar meridian for real-time bioinspired navigation through image registration. This method uses the AOP pattern to detect the solar meridian and eliminates the ambiguity between anti-solar meridian and solar meridian using the DOP pattern, resulting in an accurate heading of the observer. Simulation experiments demonstrated the superior performance of the proposed method compared to the alternative approaches. Field experiments demonstrate that the proposed method achieves real-time, robust, and accurate performance under different weather conditions with a root mean square error of 0.1° under a clear sky, 0.18° under an overcast sky with a thin layer of clouds, and 0.32° under an isolated thick cloud cover. Our findings suggest that the proposed method can be potentially used in skylight polarization for real-time and accurate navigation in GPS-denied environments.

Event-based depth estimation with dense occlusion.

Occlusions pose a significant challenge to depth estimation in various fields, including automatic driving, remote sensing observation, and video surveillance. In this Letter, we propose a novel, to the best of our knowledge, depth estimation method for dense occlusion to estimate the depth behind occlusions. We design a comprehensive procedure using an event camera that consists of two steps: rough estimation and precise estimation. In the rough estimation, we reconstruct two segments of the event stream to remove occlusions and subsequently employ a binocular intersection measurement to estimate the rough depth. In the precise estimation, we propose a criterion that the maximum total length of edges of reconstructed images corresponds to the actual depth and search for the precise depth around the rough depth. The experimental results demonstrate that our method is implemented with relative errors of depth estimation below 1.05%.

Improving energy efficiency: a highly efficient coaxial design for a laser ranging system with a splicing lens.

Light detection and ranging (LiDAR) systems have made significant contributions in different applications. The laser ranging (LR) system is one of the core components of LiDARs. However, existing coaxial LR systems suffer from low energy efficiency due to obstruction of the reflection mirror. In this study, we carefully design a laser transmitter and receiver subsystem and consequently propose a highly energy-efficient coaxial design for a time of light-based LR system, where a perforated mirror and splicing lens account for the promotion of energy efficiency. The small hole in the perforated mirror is located on the object focus of the focusing lens to ensure the laser beam will pass through the perforated mirror without obstructions. The ring-shape splicing lens, consisting of two parts, is used for laser collimation and laser reception simultaneously. Laboratory experiments proved that the proposed design eliminates the complex calibration process for noncoaxial LR systems while reaching a comparable energy efficiency, which is higher than 98%. We believe it is an economical yet efficient way to promote the energy efficiency of coaxial LR systems.

Calibration method for monocular laser speckle projection system.

This paper proposes a novel calibration method for the monocular laser speckle projection system. By capturing images of a calibration board with speckles under different poses, projector's optical axis is fitted and utilized to calibrate the rotation between the camera and projector. The translation is solved in closed form subsequently and projector's virtual image is recovered via homography. After calibration, the system can be regarded and operated as a binocular stereo vision system with speckle pattern. The proposed method is efficient and convenient, without need of reference image or high-precision auxiliary equipment. Validated by experiments on Astra-s and Astra-pro, it presents significant improvement in depth-estimation compared to the traditional method.

Two large-exposure-ratio image fusion by improved morphological segmentation.

The fusion of two large-exposure-ratio images, especially in the rocket launch field, is a challenging task because of fast-moving objects and differential features from daily scenes. Based on the large-exposure-ratio images, we propose a principle of halo formation at the boundaries of over-exposed areas. To avoid the halos in the fusion images, an improved morphological segmentation (IMS) method is developed to segment the over-exposed regions and boundaries. The IMS method is inspired by the mountain topography and builds a bridge between the 3D patches and quadratic polynomial coefficients. An improved multiscale method with segmentation in high-exposed images is proposed. In the rocket launch observation experiment, we constructed a two-camera simultaneous imaging system to avoid the dynamic scenes. The result of our proposed fusion method could best preserve the details and colors of the flames in low-exposed images and has the best subjective observation. The objective matrices also demonstrate superior edge and contrast performances over mainstream methods.

An Efficient Method for Laser Welding Depth Determination Using Optical Coherence Tomography.

Online monitoring of laser welding depth is increasingly important, with the growing demand for the precise welding depth in the field of power battery manufacturing for new energy vehicles. The indirect methods of welding depth measurement based on optical radiation, visual image and acoustic signals in the process zone have low accuracy in the continuous monitoring. Optical coherence tomography (OCT) provides a direct welding depth measurement during laser welding and shows high achievable accuracy in continuous monitoring. Statistical evaluation approach accurately extracts the welding depth from OCT data but suffers from complexity in noise removal. In this paper, an efficient method coupled DBSCAN (Density-Based Spatial Clustering of Application with Noise) and percentile filter for laser welding depth determination was proposed. The noise of the OCT data were viewed as outliers and detected by DBSCAN. After eliminating the noise, the percentile filter was used to extract the welding depth. By comparing the welding depth determined by this approach and the actual weld depth of longitudinal cross section, an average error of less than 5% was obtained. The precise laser welding depth can be efficiently achieved by the method.

[Comparative study on Sichuan yak pericardium and Australian cattle pericardium].

Currently, as the key raw material of artificial biological heart valve, bovine pericardium is mainly depend on import and has become a "bottleneck" challenge, greatly limiting the development of domestic biological heart valve. Therefore, the localization of bovine pericardium is extremely urgent. In this study, the pericardium of Sichuan yak was compared with that of Australian cattle in terms of fundamental properties and anti-calcification performance. The results demonstrated that the appearance and thickness of yak pericardium were more advantageous than the Australian one. Sichuan yak pericardium and Australian cattle pericardium had comparable performance in shrinkage temperature, mechanical test and anti-calcification test. This study preliminarily verifies the feasibility of substitution of Australian cattle pericardium by Sichuan yak pericardium and promotes the progression of bovine pericardium localization with data support.

LDV-induced stroboscopic digital image correlation for high spatial resolution vibration measurement.

Vibration measurement, particularly mode shape measurement, is an important aspect of structural dynamic analysis since it can validate finite element or analytical vibration models. Scanning laser Doppler vibrometry (LDV) and high-speed digital image correlation have become dominant methods for experimental mode shape measurement. However, these methods have high equipment costs and several disadvantages regarding spatial or temporal performance. This paper proposes a laser Doppler vibrometer induced stroboscopic digital image correction for non-contact mode shape and operational deflection shape measurement. Our results verify that single-point LDV and normal rate cameras can be used obtain high spatial resolution mode shape and operational deflection shape. Measurement frequency range is much higher than the camera capturing rate. We also show that the proposed approach coincides well with time-averaged electronic speckle pattern interferometry.

A Novel Concentric Circular Coded Target, and Its Positioning and Identifying Method for Vision Measurement under Challenging Conditions.

Coded targets have been demarcated as control points in various vision measurement tasks such as camera calibration, 3D reconstruction, pose estimation, etc. By employing coded targets, matching corresponding image points in multi images can be automatically realized which greatly improves the efficiency and accuracy of the measurement. Although the coded targets are well applied, particularly in the industrial vision system, the design of coded targets and its detection algorithms have encountered difficulties, especially under the conditions of poor illumination and flat viewing angle. This paper presents a novel concentric circular coded target (CCCT), and its positioning and identifying algorithms. The eccentricity error has been corrected based on a practical error-compensation model. Adaptive brightness adjustment has been employed to address the problems of poor illumination such as overexposure and underexposure. The robust recognition is realized by perspective correction based on four vertices of the background area in the CCCT local image. The simulation results indicate that the eccentricity errors of the larger and smaller circles at a large viewing angle of 70° are reduced by 95% and 77% after correction by the proposed method. The result of the wing deformation experiment demonstrates that the error of the vision method based on the corrected center is reduced by up to 18.54% compared with the vision method based on only the ellipse center when the wing is loaded with a weight of 6 kg. The proposed design is highly applicable, and its detection algorithms can achieve accurate positioning and robust identification even in challenging environments.

Crack Length Measurement Using Convolutional Neural Networks and Image Processing.

Fatigue failure is a significant problem in the structural safety of engineering structures. Human inspection is the most widely used approach for fatigue failure detection, which is time consuming and subjective. Traditional vision-based methods are insufficient in distinguishing cracks from noises and detecting crack tips. In this paper, a new framework based on convolutional neural networks (CNN) and digital image processing is proposed to monitor crack propagation length. Convolutional neural networks were first applied to robustly detect the location of cracks with the interference of scratch and edges. Then, a crack tip-detection algorithm was established to accurately locate the crack tip and was used to calculate the length of the crack. The effectiveness and precision of the proposed approach were validated through conducting fatigue experiments. The results demonstrated that the proposed approach could robustly identify a fatigue crack surrounded by crack-like noises and locate the crack tip accurately. Furthermore, crack length could be measured with submillimeter accuracy.

An Accurate Linear Method for 3D Line Reconstruction for Binocular or Multiple View Stereo Vision.

For the problem of 3D line reconstruction in binocular or multiple view stereo vision, when there are no corresponding points on the line, the method called Direction-then-Point (DtP) can be used, and if there are two pairs of corresponding points on the line, the method called Two Points 3D coordinates (TPS) can be used. However, when there is only one pair of corresponding points on the line, can we get the better accuracy than DtP for 3D line reconstruction? In this paper, a linear and more accurate method called Point-then-Direction (PtD) is proposed. First, we used the intersection method to obtain the 3D point's coordinate from its corresponding image points. Then, we used this point as a position on the line to calculate the direction of the line by minimizing the image angle residual. PtD is also suitable for multiple camera systems. The simulation results demonstrate that PtD increases the accuracy of both the direction and the position of the 3D line compared to DtP. At the same time, PtD achieves a better result in direction of the 3D line than TPS, but has a lower accuracy in the position of 3D lines than TPS.

A flexible multi-domain test with adaptive weights and its application to clinical trials.

The design of a clinical trial is often complicated by the multi-systemic nature of the disease; a single endpoint often cannot capture the spectrum of potential therapeutic benefits. Multi-domain outcomes which take into account patient heterogeneity of disease presentation through measurements of multiple symptom/functional domains are an attractive alternative to a single endpoint. A multi-domain test with adaptive weights is proposed to synthesize the evidence of treatment efficacy over numerous disease domains. The test is a weighted sum of domain-specific test statistics with weights selected adaptively via a data-driven algorithm. The null distribution of the test statistic is constructed empirically through resampling and does not require estimation of the covariance structure of domain-specific test statistics. Simulations show that the proposed test controls the type I error rate, and has increased power over other methods such as the O'Brien and Wei-Lachin tests in scenarios reflective of clinical trial settings. Data from a clinical trial in a rare lysosomal storage disorder were used to illustrate the properties of the proposed test. As a strategy of combining marginal test statistics, the proposed test is flexible and readily applicable to a variety of clinical trial scenarios.

Moving Object Detection under a Moving Camera via Background Orientation Reconstruction.

Moving object detection under a moving camera is a challenging question, especially in a complex background. This paper proposes a background orientation field reconstruction method based on Poisson fusion for detecting moving objects under a moving camera. As enlightening by the optical flow orientation of a background is not dependent on the scene depth, this paper reconstructs the background orientation through Poisson fusion based on the modified gradient. Then, the motion saliency map is calculated by the difference between the original and the reconstructed orientation field. Based on the similarity in appearance and motion, the paper also proposes a weighted accumulation enhancement method. It can highlight the motion saliency of the moving objects and improve the consistency within the object and background region simultaneously. Furthermore, the proposed method incorporates the motion continuity to reject the false positives. The experimental results obtained by employing publicly available datasets indicate that the proposed method can achieve excellent performance compared with current state-of-the-art methods.

Self-calibration approach to stereo cameras with radial distortion based on epipolar constraint.

In this paper, we propose a self-calibration approach to stereo cameras with radial distortion from stereo image pairs of a common 3D scene. Based on the epipolar constraint in the stereo image pair, the intrinsic and extrinsic parameters of stereo cameras are estimated synchronously with a minimum number of nine image point correspondences. It is significant within a random sample consensus (RANSAC) scheme to cope with the outliers of feature matches efficiently and robustly. Then the inliers of the stereo image pair that have been determined after RANSAC are used to optimize the calibration parameters of stereo cameras. Furthermore, more accurate calibration results can be achieved with the joint optimization of multiple stereo image pairs. Both synthetic and real data are used to evaluate the performance of the proposed method, demonstrating that our method can calibrate stereo cameras with radial distortions efficiently and accurately.

Aircraft Pose Estimation Based on Geometry Structure Features and Line Correspondences.

A robust and accurate aircraft pose estimation method is proposed in this paper. The aircraft pose reflects the flight status of the aircraft and accurate pose measurement is of great importance in many aerospace applications. This work aims to establish a universal framework to estimate the aircraft pose based on generic geometry structure features. In our method, line features are extracted to describe the structure of an aircraft in single images and the generic geometry features are exploited to form line groups for aircraft structure recognition. Parallel line clustering is utilized to detect the fuselage reference line and bilateral symmetry property of aircraft provides an important constraint for the extraction of wing edge lines under weak perspective projection. After identifying the main structure of the aircraft, a planes intersection method is used to obtain the 3D pose parameters based on the established line correspondences. Our proposed method can increase the measuring range of binocular vision sensors and has the advantage of not relying on 3D models, cooperative marks or other feature datasets. Experimental results show that our method can obtain reliable and accurate pose information of different types of aircraft.

Pose Estimation for Straight Wing Aircraft Based on Consistent Line Clustering and Planes Intersection.

Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets, and two widely separated cameras are used to acquire the pose information. Because of the large baseline and long-distance imaging, feature point matching is difficult and inaccurate in this configuration. In our method, line features are extracted to describe the structure of straight wing aircraft in images, and pose estimation is performed based on the common geometry constraints of straight wing aircraft. The spatial and length consistency of the line features is used to exclude irrelevant line segments belonging to the background or other parts of the aircraft, and density-based parallel line clustering is utilized to extract the aircraft's main structure. After identifying the orientation of the fuselage and wings in images, planes intersection is used to estimate the 3D localization and attitude of the aircraft. Experimental results show that our method estimates the aircraft pose accurately and robustly.

A Volume Measurement Method for Lunar Soil Collection Based on a Single Monitoring Camera.

In the task of lunar soil collection, estimating the volume of the collected soil is an important part of the sampling control of the lander. Due to the design constraints of the lander, there is no additional installation position for volume measurement equipment. To fully use the sensors already installed, a collected soil volume measurement method is designed in this paper based only on a single monitoring camera. This method uses a sequence of images of the collection area captured by the camera mounted on the acquisition arm to accurately reconstruct the terrain of the collection area surface before and after soil acquisition. Additionally, bi-temporal dense point clouds are reconstructed. Based on the area of change associated with soil collection, the constructed dense point clouds are compared according to the topographic characteristics of the area to estimate the volume of soil collected. Experiments show that the method is stable and reliable and can meet the requirements of actual measurement tasks.

Planar self-calibration for stereo cameras with radial distortion.

In this paper, we present a robust technique of stereo calibration using homography constraints. Our method is novel as stereo calibration is performed by solving a polynomial equation system including two radial distortion parameters, using a minimal number of five image point correspondences. This enables us to calibrate from only a pair of stereo images of a planar scene, and to provide the exact algebraic solution to the stereo calibration problem. The minimal case solution is useful to reduce the computation time and increase the calibration robustness when using random sample consensus (RANSAC) from the correspondences of the stereo image pair. Further, a non-linear parameter optimization for the intrinsic and extrinsic parameters of stereo cameras is performed using the inliers, which are determined after RANSAC. In addition, our method can achieve more robust calibration results with multiple stereo image pairs by performing joint optimization. In contrast to the previous stereo calibration methods, our method works without requiring any special hardware and has no problems with one stereo image pair, even corrupted by severe radial distortions. Finally, by evaluating our method on both synthetic and real scene data, we demonstrate that our method is both efficient and accurate for stereo calibration.