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Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Measurement technology based on machine vision has been widely used in various industries. The development of vision measurement technology mainly depends on the process of photosensitive components and the algorithm of processing a target image. In the high-precision dimension measurement of machined metal parts, the high-resolution imaging device usually exposes the cutting texture of the metal surface and affects the accuracy of measurement algorithm. At the same time, the edges of machined metal parts are often chamfered, which makes the edges of objects in the picture overexposed in the lighting measurement environment. These factors reduce the accuracy of dimensioning metal parts using visual measurements. The traditional vision measurement method based on color/gray image makes it difficult to analyze the physical quantities in the light field except for the light intensity, which limits the measurement accuracy. Polarization information can more carefully depict the edge contour edge information in the scene and increase the contrast between the foreground and the background. This paper presents a method to improve the measurement accuracy of machined metal parts by using polarization vision. The incident angle of the light source is optimized according to the complex refractive index of the metal material, and the degree of polarization image with enhanced edge contour features of the ROI (region of interest) is obtained. The high-precision measurement of cylindrical brass motor components is realized by using the method of reprojection transformation correction and maximum correlation template matching (NCC) for rough positioning, as well as the method of edge extraction and optimal fitting. The experimental results show that for copper parts with a tolerance range of ±0.1 mm, the average measurement error and maximum measurement error are within 0.01 mm, which are higher than the existing color/gray image measurement methods.

The filling with electrolyte and the subsequent wetting of the electrodes is a quality-critical and time-intensive process in the manufacturing of lithium-ion batteries. The exact processes involved in the wetting are still under investigation due to their poor accessibility. The accurate replication of the wetting phenomena in porous media can be demonstrated in other research fields by lattice Boltzmann simulations. Therefore, this paper deals with the comparison of experimental wetting and the simulative investigation of the wetting processes of lithium-ion battery materials by a lattice Boltzmann simulation. Particular attention is paid to the interfaces between the battery materials. These effects are relevant for a simulation of the wetting properties at the cell level. The experimental results show a 43% faster wetting of the interface between an anode and a separator than with only an anode. Overall, the simulation results show a qualitatively successful reproduction of the experimental wetting phenomena. In addition, the steps for a more precise simulation and the development of the Digital Twin are shown. This extension enables simulations of the electrolyte wetting phenomena in manufacturing lithium-ion batteries and the quantification of the wetting times.

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Circularly coded targets are widely used in 3D measurement, target tracking, augmented reality, and other fields as feature points to be measured. The traditional coded target recognition algorithm is easily affected by illumination changes and excessive shooting angles, and the recognition accuracy is significantly reduced. Therefore, a new coded target recognition algorithm is required to reduce the effects of illumination and angle on the recognition process. The influence of illumination on the recognition of coding targets was analyzed in depth, and the advantages and disadvantages of traditional algorithms are discussed. A new adaptive threshold image segmentation method was designed, which, in contrast to traditional algorithms, incorporates the feature information of coding targets in the determination of the image segmentation threshold. The experimental results show that this method significantly reduces the influence of illumination variations and cluttered backgrounds on image segmentation. Similarly, the influence of different angles on the recognition process of coding targets was studied. The coding target is decoded by radial sampling of the dense point network, which can effectively reduce the influence of angle on the recognition process and improve the recognition accuracy of coding targets and the robustness of the algorithm. In addition, further experiments verified that the proposed detection and recognition algorithm can better extract and identify with high positioning accuracy and decoding success rate. It can achieve accurate positioning even in complex environments and meet the needs of industrial measurements. [ABSTRACT FROM AUTHOR]

[Objectives]The spatial position of carrier-based aircraft on the deck is required before take-off. Visual measurement is a high-precision and high-efficiency automated measurement method.[Methods]Therefore, a spatial positioning scheme for the carrier-based aircraft based on visual measurement is proposed in this paper. Firstly,the "Visual Measurement System-Deck Plane" relative position calibration method is introduced;secondly,based on the collinear relationship of "Visual Measurement Camera-Imaging Center-Fuselage Cooperation Logo",the position of the cooperation logo relative to the visual measurement system is calculated;finally,on this basis,the fuselage fixed cooperation logo is identified as a position transfer relay station to obtain the non-visual environment "Visual Measurement System-Airborne Inertial Navigation" transfer measurement model.[Results]The results of the visual measurement experiments show that the target spatial positioning result based on visual measurement is better than 0.3 m.[Conclusion]This scheme is expected to enable more carrier-based aircraft sorties to obtain spatial positioning information with higher precision before take-off.

In many measurement applications using multicameras, there is often a nonoverlapping field of view (nFOV) between multicameras. It benefits greatly from having all of the cameras unified in a single coordinate frame by means of common spatial constraints. However, it is very difficult to establish common spatial constraints for accurate and quick calibration of the extrinsic parameters between multicameras in the case of long working distance, asymmetric working angle, or limited working space. To overcome these issues, we propose a flexible calibration method using a camera rig, which can be easily modeled as a hand–eye calibration problem and solved by only several sets of calibration images. To further improve the calibration accuracy, the camera intrinsic parameters, lens distortion coefficients, and extrinsic parameters are optimized simultaneously, similar to binocular calibration. However, this causes calculation instability of multiparameters. We extend the epipolar constraint to two images with an nFOV and add it into the optimization objective function together with the reprojection error, which ensures the basic consistency of intrinsic parameters before and after optimization, and reduce the fluctuation caused by the number of images involved in calibration. Experiments and application have proved that the proposed new methods are feasible and effective. [ABSTRACT FROM AUTHOR]

Flexible membrane structure is generally used as wing skin for long-endurance low-speed aircraft, such as solar aircraft, to control the structure weight within the allowable range. Predictably, the elastic deformation of the membrane under complex loads will cause uncertain impacts on the aerodynamic performance. The existing research indicates that the deformation of the membrane wing is helpful to improve the aerodynamic characteristics. However, most of the research objects are non-thickness membrane wings. In this paper, wind tunnel experiments are performed on double membrane wings. The experiment results indicate that the membrane deformation behavior is related to the surface curvature distribution and will change the camber and thickness of the airfoil. The deformation has little effect on lift but has a significant effect on drag and pitching moment. On this basis, a high-precision fluid structure coupling analysis method for the wider range of research is introduced. The numerical analysis indicates that the deformation can delay the stall angle by 1°. Furthermore, based on the numerical results, suggestions on prestress setting during membrane skin laying are provided, and the numerical simulation results of two flexible skin wings are compared. The research results of this paper provide a scientific basis for the aerodynamic design and analysis of long-endurance low-speed aircraft.

This article proposes a novel visual measurement framework, multimodule cascaded deep neural network (MMC-DNN), to achieve accurate, reliable, and cost-effective vehicle positioning in complex urban environments. The MMC-DNN is inspired by the mechanism of the human eyes’ lateral positioning, which consists of three modules called siamesed fully convolutional network (S-FCN), skip-connection fully convolutional autoencoder (SC-FCAE), and multitask neural network regressor (MT-NNR), respectively. The S-FCN is first designed to accurately detect the road area. Then, the segmented road was executed inverse perspective mapping and the result is fed to the developed SC-FCAE for extracting equivalent positioning features. Furthermore, the MT-NNR is proposed to efficiently estimate lateral position and yaw angle with the help of a road map. Based on the estimation results, the MEMS INS/GPS integration is significantly augmented by extended Kalman filter. Experimental results validate the effectiveness of the proposed framework in enhancing positioning performance. [ABSTRACT FROM AUTHOR]

Vision-based measurement and prediction (VMP) are the very important and challenging part for autonomous robotic manipulation, especially in dynamic and uncertain scenarios. However, due to the potential limitations of visual measurement in such an environment such as occlusion, lighting, and hardware limitations, it is not easy to acquire the accurate positions of an object as the observations. Moreover, manipulating a dynamic object with unknown or uncertain motion rules usually requires an accurate prediction of motion trajectory at the desired moment, which dramatically increases the difficulty. To address the problem, we propose a time granularity-based vision prediction framework whose core is an integrated prediction model based on multiple [i.e., long short-term memory (LSTM)] neural networks. At first, we use the vision sensor to acquire raw measurements and adopt the preprocessing method (e.g., data completion, error compensation, and filtering) to turn raw measurements into the standard trajectory data. Then, we devise a novel integration strategy based on time granularity boost (TG-Boost) to select appropriate base predictors and further utilize these history trajectory data to construct the high-precision prediction model. Finally, we use the simulation and a series of dynamic manipulation experiments to validate the proposed methodology. The results also show that our method outperforms the state-of-the-art prediction algorithms in terms of prediction accuracy, success rate, and robustness. [ABSTRACT FROM AUTHOR]

This study analyzed the effects of spectral overlays on ocular motility during reading among a clinical group of children and adolescents experiencing visual–perceptual distortions of text. We reviewed the records of 323 eye-hospital patients diagnosed with visual stress and divided this participant sample into two age-based cohorts: children (n = 184; Mean [ M ] age = 10.1, standard deviation [ SD ] = 1.3 years) and adolescents (n = 139; M age = 14.6, SD = 1.5 years). We used a Visagraph III Eye-Movement Recording System to record ocular motor efficiency while reading with and without spectral overlays, and we examined the following parameters: (a) Fixations, (b) Regressions, (c) Span of Recognition, (d) Reading Rate, (e) Relative Efficiency, and (f) Comprehension. Our results showed that using one or some combination of 10 participant-selected spectral overlays immediately and significantly (p <.001) reduced the number of Fixations and Regressions per 100 words, while there were significant (p <.001) gains in positive factors such as Span of Recognition, Reading Rate, Relative Efficiency, and Comprehension. Our findings indicate that spectral filtering can be an effective tool for helping many young patients who experience visual–perceptual distortions while reading. Future expanded research employing eye-tracking technology is clearly needed. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A template matching (TM) algorithm has been widely employed in a visual inspection process of wafer-level flip-chip packaging, but the structures of traditional TM algorithms are always direct feedforward, which leads to the difficulty in achieving fast speed and high accuracy at the same time. The motivation of this article is to combine the ability to enable the chip visual measurement running in a fast-speed and high-accuracy manner. First, a novel self-feedback intelligent template matching (SFI-TM) structure is proposed, which can enable the intermediate information in the matching process to be fully utilized. The intelligent speed and resolution regulation rules are combined to construct the SFI-TM algorithm. Then, the reliability and robustness of the SFI-TM algorithm are theoretically analyzed to make sure it works in a stable manner. Finally, a series of practical chip alignment visual inspection experiments, including parameter testing, comparing experiments with the other five proposed visual detection algorithms, and robustness testing, are carried out in detail, respectively. The experimental results indicate that the SFI-TM algorithm can achieve the highest average measurement accuracy (1.08  $\mu$ m) with almost the same measurement speed as fast as Tiny YOLOv2, and that it can resist the brightness variation from $-$ 20 to 30 gray value, the pepper–salt noise with a density of 0.5/pixel, and the Gaussian noise with a large variance of 2.5. In addition, it has good robustness against blurring and distortion of images under the dynamic speed motion processes. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a position and orientation measurement method for bolter-miner based on double-screen visual target is proposed, in which the target is composed of two industrial cameras and photosensitive surfaces. The point-cloud data of 2D–3D coordinates is established by using the method of grid calibration and index. Consequently, the posture parameters of bolter-miner and the horizontal/vertical offset distance of machine body key-points relative to the laneway tunneling axis (LTA) can be finally calculated with the prior information of the indicating laser. The experimental results show that the static repeatability measurement accuracy of laser-spot 3D coordinate is 0.07 mm, the repeatability measurement accuracy of yaw angle is better than 0.01°, the absolute measurement error of yaw angle is less than 0.05°, and the measurement error of horizontal/vertical offset distance are less than 5 mm. The experiment results proved that this method is practicable for application of the guidance and localization for bolter-miner. • This method can be applied in the coal mine industry with high accuracy and lower production cost. • The method of grid calibration and index are employed to build the point-cloud data of laser-spot 2D–3D coordinates. • The special structure of target can greatly improve the ability of anti-dust interference in harsh underground environment. • This method is easy to operate and can effectively improve the working efficiency of roadway excavation. [ABSTRACT FROM AUTHOR]

To improve the measurement precision of the structured light target angle, this paper studies the relation between the structured light system parameters and measurement accuracy of the angle. Firstly, the main system structure parameters influencing the angle measurement precision are analyzed based on the structured light measurement principle; secondly, simulation research on the laws of how the structured parameters influence the angle measurement precision are conducted, and the optimized range of values of the structured parameters is proposed; finally, the experimental studies show that, the optimized parameters can improve the angle measurement precision effectively, which lays the design foundation for later improvement schemes of the structured light 3D four-wheel alignment instrument.

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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In this paper, a visual-based method is proposed for the table tennis robot to estimate the hitting point from the opponent, which can provide a better understanding of the opponent, and thus improve the responsiveness of the table tennis robot. As an essential manifestation of opponent hitting behavior, the information of hitting point includes not only the motion status variation of the ball before and after being hit, but also the racket pose at the hitting moment. To solve this problem, the trajectories of the ball before and after being hit are first predicted based on visual measurement and the motion model of the ball. The racket trajectory of the opponent is then derived by a self-adaptive threshold selection scheme and a multifilter. Considering that the ball and racket trajectories are not absolutely precise, an optimized solution is proposed to compute the hitting point from the opponent. To the best of our knowledge, the proposed approach is the first one that could achieve a fast estimation of the hitting point from the opponent with a satisfactory resolution. The effectiveness of the proposed approach is verified by experiments. [ABSTRACT FROM PUBLISHER]

Target with concentric circles has been widely used in artificial target and camera calibration of visual measurement systems. The accuracy of concentric circle target directly affects the accuracy of vision measurement system. In this study, an improved method for accurate positioning of concentric circles projection center is proposed. Compared with similar methods, the proposed method has high accuracy and does not need to know the radius of the concentric circle in advance. The influence of inner and outer circle radius and rotation angle of concentric circles on the position error of circular projection center is analyzed by single camera experiment. The experimental results show that the position error of this method is lower than that of similar methods. The concentric circles calibration board is designed as an application to calibrate the binocular vision system. It is shown that the calibration results of the camera's intrinsic parameters are almost the same as those of PPAGC. However, compared with PPAGC, the total projection error of the left camera is reduced by 30.77% and that of the right camera by 28.29%. • Firstly, an accurate ellipse detection method is proposed. • Secondly, the method of detecting and removing outliers in the process of image edge detection is proposed. • Thirdly, a simple method to determine the projection center of concentric circles is proposed. [ABSTRACT FROM AUTHOR]

The internal parameters is one of the important calibration parameters of visual measurement, which shows the accurate corresponding relation of the space point and the imaging point in computer image coordinate. Based on fiber optic imaging characteristics, the paper proposed the circular array targets and sub-pixel threshold segmentation algorithm to extract target feature points as to help the follow-up the accurate calibration of camera internal parameters. In contrast to some commonly uesd algorithm to extract the sub-pixel edge contour using interpolation and fitting, the proposed sub-pixel threshold segment algorithm is more small computational complexity and execution time. The experimental results show that the camera internal parameters have been obtained precisely with low execution time, which provides important guarantee for subsequent fiber length measurement based on visual measurement. [ABSTRACT FROM AUTHOR]

The thermal condition and fluid flow in weld pool determine the formation of humping bead in high speed gas metal arc welding. An external magnetic field is utilized to control the fluid flow and heat transfer in weld pool to suppress the humping bead formation. The measurements of temperature field and molten metal flow on the weld pool surface are conducted under the conditions without and with the external magnetic field. When the external magnetic field is applied, the temperature distribution in the weld pool is more uniform. The backfilling of molten metal and fluid flow are improved, and the longitudinal velocity of backward molten metal flow is reduced. The external magnetic field not only adds a resistance but also decreases the driving force for the flow of the backward molten metal in weld pool so that the momentum of the backward molten metal flow is reduced and the humping bead is suppressed. [ABSTRACT FROM AUTHOR]

When a space robotic arm deploys a payload, usually the pose between the cooperative target fixed on the payload and the hand-eye camera installed on the arm is calculated in real-time. A high-precision robust visual cooperative target localization method is proposed. Combing a circle, a line and dots as markers, a target that guarantees high detection rates is designed. Given an image, single-pixel-width smooth edges are drawn by a novel linking method. Circles are then quickly extracted using isophotes curvature. Around each circle, a square boundary in a pre-calculated proportion to the circle radius is set. In the boundary, the target is identified if certain numbers of lines exist. Based on the circle, the lines, and the target foreground and background intensities, markers are localized. Finally, the target pose is calculated by the Point-3-Perspective algorithm. The algorithm processes 8 frames per second with the target distance ranging from 0.3m to 1.5 m. It generated high-precision poses of above 97.5% on over 100,000 images regardless of camera background, target pose, illumination and motion blur. At 0.3 m, the rotation and translation errors were less than 0.015° and 0.2 mm. The proposed algorithm is very suitable for real-time visual measurement that requires high precision in aerospace. [ABSTRACT FROM AUTHOR]

Vibration measurement based on computer vision has been extensively studied and considered as a wide-range, non-contact measurement method. In this paper, the principle of vibration measurement using out-of-plane vision has been investigated under conventional imaging condition. A measurement model for out-of-plane vision has also been demonstrated. Combined the out-of-plane vision measurement model with the optical flow motion estimation principle, a novel model of optical flow tracking method for vibration detection based on out-of-plane vision has been proposed. It enables the identification of vibration parameters without image feature extraction. Visual vibration detection experiment has been conducted with a cantilever beam and a motor cover. Experimental results have been rigorously compared with finite element simulation to verify the efficacy of the proposed method. It shows that this method can effectively identify vibration parameters of the structure without image feature extraction. [ABSTRACT FROM AUTHOR]

A new visual measurement method is proposed to estimate three-dimensional (3D) position of the object on the floor based on a single camera. The camera fixed on a robot is in an inclined position with respect to the floor. A measurement model with the camera's extrinsic parameters such as the height and pitch angle is described. Single image of a chessboard pattern placed on the floor is enough to calibrate the camera's extrinsic parameters after the camera's intrinsic parameters are calibrated. Then the position of object on the floor can be computed with the measurement model. Furthermore, the height of object can be calculated with the paired-points in the vertical line sharing the same position on the floor. Compared to the conventional method used to estimate the positions on the plane, this method can obtain the 3D positions. The indoor experiment testifies the accuracy and validity of the proposed method. [ABSTRACT FROM AUTHOR]

Visual techniques were used to identify the wave force on a large-scale vertical cylinder for the first time in this study by tracking the dynamic waterlines around the cylinder. Experimental validation of the proposed method with two types of waves, regular and irregular, was conducted in a wave flume. Four cameras were used to capture images synchronously, and the dynamic waterlines around the cylinder were identified using a grayscale gradient of pixels. Based on the potential theory, the wave force, including the linear and part of the second- and higher-order force components, was identified using recursive least squares (RLS) in real-time. The identified wave force agreed well with the wave force measured by the load cells, particularly the linear wave forces. The identified results could be significantly improved by considering the nonlinear wave forces. The proposed method has broad applications for laboratory measurements of wave loads on cylindrical structures. • Visual techniques are used to identify the wave force on a cylinder for the first time by tracking the dynamic waterlines. • Comparisons between the identified and measured wave force showed high accuracy of the proposed method. • By considering high-order wave components, nonlinear wave forces in the identified results were greatly improved. • The proposed method has broad applications in laboratory measurements of wave force on cylindrical structures. [ABSTRACT FROM AUTHOR]

Estimating image vanishing points has many applications in the computer vision field, such as robotic navigation, visual measurement, camera calibration, 3D reconstruction and augmented reality, which requires a balance between accuracy and rate. In this paper, we present an algorithm to accurately and efficiently detect vanishing points and classify lines through the clustering method and binary particle swarm optimization (BPSO). First, lines are clustered according to their slope angles based on an iterative BPSO process, since parallel lines, in a medium-to-long range scene, present similar slopes. The solutions are continuously evaluated using multiple factors, such as the number and length of the line segments and their distance to the related vanishing points. The coefficient of variation is applied to weigh these factors. As a result, all possible non-orthogonal vanishing points in the image are directly detected, irrespective of the camera calibration parameters to avoid mapping segments on the Gaussian sphere. Compared with other algorithms on the York Urban Database, the proposed algorithm exhibits significant performance improvements. [ABSTRACT FROM AUTHOR]

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For center deviation of space circular mark in the perspective projection transformation process, a novel method is proposed in this paper to locate the real projection center precisely based on the theory of analytic geometry and spatial perspective. First, we analyze the spatial circle error of perspective projection transforms generated and gives relevant basic principles. Then the detailed implementation of the algorithm and the specific steps are presented. Finally through the experiments verify the effectiveness of the method. Simulation and experimental results indicate that this method can achieve the actual projection point precise positioning of the space circular target. The algorithm does not require additional complex constraints and has good robustness; therefore it has a wide range of practical engineering application value. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Hebei University of Science & Technology is the property of Hebei University of Science & Technology, Journal of Hebei University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To fulfill the need of measurement on the small bore's interior features, a specially designed optical transmission component is adopted to divert exterior illumination into the interior of small bore and to export the interior image. This study has surpassed the traditional mode and achieved the exterior placement of the measurement sensors to make it possible for the measurement in narrow space. To fulfill the need of measurement on small bores in different position and direction, a new flexible in-line measurement system is set up utilizing the movement platform of industrial robots. Firstly, the design of the measurement system is proposed based on analysis of the preliminary method, and the flow of the work is given. Then, the question of alignment between sensor and sample is analyzed in detail, and a novel, reasonable method of aligning is given. Based on the aligned system, the measuring experiment is carried out on 0.6 mm, 1.0 mm and 2.0 mm simulated defects on interior wall of 10 mm diameter bore, and the standard deviation is almost less than 0.01 mm. The experimental results show that the system is valid and able to accomplish the feasible, on-line measurement. [ABSTRACT FROM AUTHOR]

Vanishing points (VPs) are crucial for inferring the three-dimensional structure of a scene and can be exploited in various computer vision applications. Previous VP detection algorithms have been proven effective but generally cannot guarantee a strong performance in both accuracy and computational time. We propose an artificial bee colony algorithm called dynamic clustering artificial bee colony (DCABC) that accurately and efficiently detects VPs in the image plane. The task is regarded as a dynamic line-clustering problem, and the line clusters are initialized by their orientation information. Inspired by the foraging behavior of bees, DCABC selects the clustering center and reclassifies the line segments based on a distance criterion until the terminating condition is met. The optimal line clusters determine the estimated VP. The dissimilarity among solutions is measured by the Hamming distance between two binary vectors, which simplifies the new solution construction. The performances of the proposed and existing algorithms are evaluated on the York Urban database. The results verify the efficiency and accuracy of our proposed algorithm. [ABSTRACT FROM AUTHOR]

• A visual inspection method for delamination of carbon fiber reinforced plastic (CFRP). • Robust circle parameter fitting considering the distribution characteristics of outlier points. • Multi-scale adaptive threshold for delamination extraction. • Statistical quality description factor for quantification of multi-dimensional information. Inspection the delamination of composite components is essential to ensure the safety of aircraft in service. Vision inspection has great potential for the drilling quality inspection of large composite components. However, stable extraction and accurate quantification of delamination are extremely challenging, due to the characteristics of low contrast, varying morphology, and random distribution of delamination. To address this problem, robust delamination extraction algorithm and integrated evaluation method are proposed. The extraction of delamination is achieved by contour extraction, robust circle fitting, and adaptive threshold segmentation. Based on this, the statistical quality description factor Q d - s is designed to quantify multi-dimensional information of delamination. Finally, the effectiveness of the proposed method is demonstrated. The experimental result shows that the proposed method outperforms traditional methods, which is expected to become a general technique for the inspection of delamination in the manufacturing process of CFRP. [ABSTRACT FROM AUTHOR]

Due to the influence of many factors in monocular vision pose measurement, the reliability of pose measurement results needs to be evaluated by uncertainty. The difficulties of the traditional guide to the expression of uncertainty in measurement (GUM) method in actual pose evaluation are analyzed, and the adaptive Monte Carlo method (AMCM) is used to evaluate the uncertainty of pose results. According to the mathematical model of pose measurement, the factors affecting pose results are analyzed in detail. The uncertainty evaluation model is established by the error traceability method and the distribution of uncertainty components is analyzed reasonably. Both the Monte Carlo method (MCM) and AMCM are used to evaluate the uncertainty of pose results. The feasibility and effectiveness of the AMCM evaluation method are verified. The experimental results show that MCM and AMCM, as the supplement of the GUM method, can well solve the problem of pose evaluation in the actual measurement system. However, AMCM is more convenient and efficient than MCM to solve the problem of too large or too small sampling times. [ABSTRACT FROM AUTHOR]

A novel non-contact dental 3D points cloud measurement system based on grating projection is proposed in this paper. The system has the key functions of calibration, phase unwrapping and conversion of two-dimensional image to the 3D point cloud and so on, and it can provide three-dimensional graphics of the dental wax with rotations and translation to observe and measure the various parts of dental wax surface. The system can be used as a useful test and analysis tool for clinical medicine teaching and researches. [ABSTRACT FROM AUTHOR]

A high-speed monocular vision system is established to track the racket trajectory for estimating the spinning ball initiated by a human. A new fast and robust method is proposed to extract the feature sequence of a racket's pose during the process of striking. Considering the complexity of the working environment and fast movement of the racket, a novel corner extraction algorithm with good robustness and high efficiency is presented, which mainly consists of two parts, i.e., target segmentation and line detection. Then PnP-based algorithm is adopted to get the rough pose of the racket, which is then optimized by orthogonal iteration algorithm to guarantee the orthogonality of the racket's orientation matrix. In order to classify the spinning mode of the ball with a higher accuracy, the racket's movement is represented by the sequence of normal vector of the racket's surface. Experiments are thoroughly conducted to verify the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]