Binocular Stereo Vision Measurement Research Articles

System Structural Error Analysis in Binocular Vision Measurement Systems

A binocular stereo vision measurement system is widely used in fields such as industrial inspection and marine engineering due to its high accuracy, low cost, and ease of deployment. An unreasonable structural design can lead to difficulties in image matching and inaccuracies in depth computation during subsequent processing, thereby limiting the system’s performance and applicability. This paper establishes a systemic error analysis model to enable the validation of changes in structural parameters on the performance of the binocular vision measurement. Specifically, the impact of structural parameters such as baseline distance and object distance on measurement error is analyzed. Extensive experiments reveal that when the ratio of baseline length to object distance is between 1 and 1.5, and the angle between the baseline and the optical axis is between 30 and 40 degrees, the system measurement error is minimized. The experimental conclusions provide guidance for subsequent measurement system research and parameter design.

DIC measurement method based on binocular stereo vision for image 3D displacement detection

The deformation detection of large machinery is usually achieved using three-dimensional displacement measurement. Binocular stereo vision measurement technology, as a commonly used digital image correlation method, has received widespread attention in the academic community. Binocular stereo vision achieves the goal of three-dimensional displacement measurement by simulating the working mode of the human eyes, but the measurement is easily affected by light refraction. Based on this, the study introduces particle swarm optimization algorithm for target displacement measurement on Canon imaging dataset, and introduces backpropagation neural network for mutation processing of particles in particle swarm algorithm to generate fusion algorithm. It combines the four coordinate systems of world, pixel, physics, and camera to establish connections. Taking into account environmental factors and lens errors, the camera parameters and deformation coefficients were revised by shooting a black and white checkerboard. Finally, the study first conducted error analysis on binocular stereo vision technology in three dimensions, and the relative error remained stable at 1 % within about 60 seconds. At the same time, three algorithms, including the spotted hyena algorithm, were introduced to conduct performance comparison experiments using particle swarm optimization and backpropagation network algorithms. The experiment shows that the three-dimensional error of the fusion algorithm gradually stabilizes within the range of [–0.5 %, 0.5 %] over time, while the two-dimensional error generally hovers around 0 value. Its performance is significantly superior to other algorithms, so the binocular stereo vision of this fusion algorithm can achieve good measurement results.

Research on a measurement method for spatio-temporal distribution of fragments based on a high-speed camera network

To reliably measure multiple spatio-temporal distribution parameters of fragments in the blast field, a measurement method for spatio-temporal distribution of fragments based on a high-speed camera network is proposed. The method is based on the principle of binocular stereo vision measurement and consists of four steps: fragment image acquisition, target detection of multi-view images, fitting of motion trajectory, and calculation of the spatio-temporal distribution parameters. The test results demonstrate that the method can simultaneously measure multiple parameters in the intersecting field of view. Compared with the measurement results of the array target, the absolute value of the measurement relative error of velocity was less than 1.5%, and the measurement results of scatter angle and distribution density were consistent. It indicates that the measurement results of the proposed method are reliable, and the method is a feasible and effective measurement method for spatio-temporal distribution parameters of fragments in the explosion filed.

BSV System with MSC and Its Application in the Measurement of Surface Cracks

In this paper, we have proposed a flexible noncontact crack‐size measurement method that can realize binocular stereo vision measurement with only a single camera. On the premise that the camera’s intrinsic parameters have been accurately calibrated, we use a camera to collect the image of the crack from two directions. Then, we calculate the motion parameters using the collected images from the camera in different positions. In addition, Canny algorithm is used to extract the edge pixels of crack images. Finally, we establish the binocular stereo vision model for crack measurement according to the camera parameters, the motion parameters, and the edge information of crack images. Thus, we can measure the crack size through this model. Experimental results show that the measurement error is less than 5% under a distance of 2 meters, which can effectively prove the precision of the proposed method. In addition, our method only uses a single camera. Compared with the traditional binocular stereo vision method, this method is not only flexible but also more economical.

Method for improving the measurement accuracy of binocular stereo vision in a scattering environment.

In the scattering environment, binocular stereo vision measurement technology produces large errors due to the change of refractive index of the imaging light path and the decrease in target image contrast. To address this problem, this paper proposes a method for improving the measurement accuracy of binocular stereo vision in a scattering environment combined with polarization imaging theory. First, scattering images with different polarization directions are obtained and filtered by a Gaussian low-pass filter to calculate the degree of polarization and angle of polarization. Then, the scattered light intensity is calculated by using polarization information to obtain images after removing the scattering. Second, feature extraction and matching are carried out for the images after scattering removal. Finally, the target is measured based on the binocular stereo vision measurement model. The experimental results show that when the scattering concentration is high enough, the conventional method can no longer perform measurement, but the method proposed in this paper can still obtain the target parameters at this time, and can also improve measurement accuracy by at least 46.30%. In conclusion, the proposed method provides a valuable reference to improve the accuracy of binocular stereo vision measurement in a scattering environment by reducing the interference of scattering light.

Application of integrated binocular stereo vision measurement and wireless sensor system in athlete displacement test

Based on binocular stereo vision measurement and wireless sensing theory, this paper studies the measurement and analysis methods of athletes' movement displacement parameters. The main purpose is to explore the relationship between sports biomechanical parameters. The analysis reveals the laws of athletes 'movements, and provides theoretical guidance on athletes' attitude recognition and physical training. Based on the principle of binocular stereo vision, a non-contact displacement measurement system was developed. The displacement measurement system uses template matching to extract the image coordinates of the measurement points and restore the spatial coordinates of the measurement points through European 3D reconstruction, which improves the practicality of the measurement system. In the cantilever beam vibration test, the traditional displacement sensor and binocular image displacement measurement system are used to simultaneously measure the cantilever beam displacement. The experimental results show that the integrated displacement measurement system in this paper has higher accuracy and better stability.

The Application of Visual Sensors in the Artistic Design of College Campus Landscape

The research purpose is to solve the problems of low efficiency, low accuracy, and high cost of traditional environmental landscape mapping and landscape volume measurement methods in the artistic design of college campus landscape and make up the defects that the traditional campus monitoring is vulnerable to adverse weather, which results in low monitoring accuracy. Primarily, a binocular stereo vision measurement based on Scale Invariant Feature Transform (SIFT) matching algorithm is proposed, which can realize accurate collection of environmental spatial information and measurement of landscape volume without contact in the process of campus landscape design. Then, the visual monitoring system of college landscape based on the Internet of Things (IoT) is constructed to realize real‐time monitoring and early warning of human damage to campus landscape. The proposed method is verified by actual measurement of different objects and simulation experiments using simulation software. Ultimately, the application of visual sensors in artistic design of college campus landscape is analysed by literature analysis. The results show that (1) the error of the improved binocular stereo vision measurement designed here is 52.32% and 59.69% lower than that of the traditional measurement method when measuring the same object with different volumes and the volumes of different objects, respectively, which indicates that the measurement accuracy of the new method is higher. (2) The proposed landscape visual monitoring method based on IoT improves the image recognition accuracy by 21% compared with the traditional digital image monitoring method. The average recognition time is shortened by 12 ms, which ensures the accuracy and improves the recognition efficiency. (3) Through the analysis of existing literature, it is found that the binocular stereo vision sensor can be used to monitor the whole process of landscape construction in real time. The sensor can be combined with social networks, mobile terminals, and physiological monitoring equipment to comprehensively analyse and evaluate people’s preference for campus landscape. The proposed method has broad application prospects in campus landscape design, construction, and maintenance. The research purpose is to provide important technical support for the improvement of the overall image of the college campus and even the city for the design of landscape environment and the technical upgrading of maintenance work in the college campus.

Binocular stereo vision calibration based on constrained sparse beam adjustment algorithm

In order to realize high-precision three-dimensional measurement of railway train head, a high-precision camera calibration algorithm for binocular stereo vision system based on constrained sparse beam adjustment is proposed in this paper. By analyzing the digital model of binocular vision and the principle of three-dimensional measurement, a binocular stereo vision measurement system based on time-domain coding is built. The edge preservation filtering algorithm based on mean square deviation is used to denoise and filter the visual image. The image is enhanced by histogram equalization. A FAST algorithm based on accelerated segmentation detection is proposed to extract feature information. To solve the problem of camera calibration, a binocular vision calibration method based on coplanar intersecting circle is proposed. The coordinates of circular points are calculated by using the extracted elliptic contour of the intersecting circle, and then the internal parameters of the two cameras and the position relationship between them are obtained. The calibration algorithm needs no manual intervention and has high accuracy. Aiming at the distortion correction, the camera calibration is transformed into a global optimization problem, and the sparse beam adjustment algorithm based on constraints is used to optimize the parameters. Compared with Zhang's calibration method, the results show that the average absolute relative error of the parameters in the two cameras is less than 3.45e−6, the average re-projection error is about 0.1 pixels, and the data accuracy is high, which proves the feasibility and theoretical correctness of the experimental method of the system.

Fuzzy neural network vibration control on a piezoelectric flexible hinged plate using stereo vision detection

Vibration control on a two-connected piezoelectric flexible hinged plate is investigated, using a fuzzy neural network algorithm based on binocular vision measurement. As for vision sensing, a method to acquire vibration signals of the low frequency bending and torsional mode is investigated. To damp out the residual vibration quickly, the fuzzy neural network is applied to ensure the stability and control effect adaptively. To verify the stereo vision measurement method and the applied controller, an experimental setup of the piezoelectric flexible hinged plate with a binocular stereo vision is constructed. Experiments are conducted by using the binocular stereo vision measurement system and the adopted controller. The experimental results demonstrate the feasibility of the visual measurement method. Furthermore, the designed fuzzy neural network can attenuate the bending and torsional vibrations quickly, in comparison with proportional and derivative control, particularly for the small-level residual vibration.

Stereo vision–based non-contact dynamic measurement method for vehicle braking time sequence

The braking stability of semi-trailer train is directly related to the safety of driving. The braking time sequence of vehicle in braking process directly determines the braking stability of the vehicle. To overcome the limitations of the existing technology, this paper proposes a novel non-contact vehicle braking time sequence measurement method. The proposed method is based on binocular stereo vision that has high precision, high efficiency and low cost. First, the binocular stereo vision measurement principle is introduced, the camera is calibrated by three-dimensional target and the Levenberg–Marquardt algorithm is used to optimize the calibration parameters. Then, a series of image processing techniques are used to extract the wheel marker and perform three-dimensional coordinate reconstruction. Finally, the universality and the applicability of the proposed method are verified by conducting repetitive experiments and accuracy experiments for the same vehicle and different types of vehicles according to the designed experimental process and the established evaluation index. The experimental results show that the method proposed in this paper can achieve fast detection, with high accuracy and good repeatability. Moreover, the method can be extended to various types of vehicles.

Precision calibration method for binocular vision measurement systems based on arbitrary translations and 3D-connection information

Binocular vision systems play an important role in computer vision, and high-precision system calibration is a necessary and indispensable process. In this paper, an improved calibration method for binocular stereo vision measurement systems based on arbitrary translations and 3D-connection information is proposed. First, a new method for calibrating the intrinsic parameters of binocular vision system based on two translations with an arbitrary angle difference is presented, which reduces the effect of the deviation of the motion actuator on calibration accuracy. This method is simpler and more accurate than existing active-vision calibration methods and can provide a better initial value for the determination of extrinsic parameters. Second, a 3D-connection calibration and optimization method is developed that links the information of the calibration target in different positions, further improving the accuracy of the system calibration. Calibration experiments show that the calibration error can be reduced to 0.09%, outperforming traditional methods for the experiments of this study.

Improved camera calibration method based on perpendicularity compensation for binocular stereo vision measurement system.

High-precision calibration of binocular vision systems plays an important role in accurate dimensional measurements. In this paper, an improved camera calibration method is proposed. First, an accurate intrinsic parameters calibration method based on active vision with perpendicularity compensation is developed. Compared to the previous work, this method eliminates the effect of non-perpendicularity of the camera motion on calibration accuracy. The principal point, scale factors, and distortion factors are calculated independently in this method, thereby allowing the strong coupling of these parameters to be eliminated. Second, an accurate global optimization method with only 5 images is presented. The results of calibration experiments show that the accuracy of the calibration method can reach 99.91%.

Baggage Specification Detection Based on the Binocular Vision

To the baggage specification automatically detection problem of self-service bag drop system, a baggage size detection algorithm based on stereo vision is proposed. The algorithm is based on binocular stereo vision measurement principle. Firstly, the canny edges of baggage image are extracted as the feature points. With the disparity gradient constraint and epipolar constraint, Stereo matching algorithm based on edge features is proposed, meanwhile, the two images play a symmetric role to ensure the reliability of matching in the matching process. The coordinates of the three dimensional points are derived with approximation of the middle point of the common perpendicular line in different planes. Experimental results show that the proposed algorithm can detect the baggage specification with appropriate accuracy.

Research on Light Pen Measuring System

Under the current situation of the rapid development of major equipment and technology, the research on measurement equipment, suitable for requirement of large-size application, is urgency and important. A light pen measuring system based on binocular stereo vision measurement principle is researched. The composition and working principle of the system are analyzed. Subpixel marginal fitting method is adopted to obtain the precise position of the center coordinates of the point of the coded marks. A mathematical model of the camera is Established, and the corresponding relations between the three-dimensional coordinates of the mark points in space and the two-dimensional coordinates of the same points in the image are deduced. In order to improve the speed and accuracy of image matching, the light reflection coded mark stickers are adopted as the marks of the light pen for imaging. The research on the key technologies of the light pen measuring system provides a theoretical basis for the further striking of three-dimensional coordinates of the space point, for the 3D reconstruction of the space model, and for the realization of software technology .

Three-dimensional sheet metal continuous forming process based on flexible roll bending: Principle and experiments

To effectively manufacture three-dimensional sheet metal parts with various curvatures produced in small batch quantities, continuous sheet metal forming, a new flexible forming technology is being developed. This process employs an upper flexible roll and two lower flexible rolls as a forming tool, and the shape of a flexible roll can be changed in vertical direction. With the rotation of flexible rolls, the sheet metal is bent in longitudinal and transverse directions simultaneously and is formed continuously. In the present study, the three-dimensional surface of formed part is described by sweep surface based on the characteristic of the forming process and the arc-length parametric equation for describing continuous forming part is developed. The three-roll bending deformation of sheet metal in longitudinal direction is analyzed and the longitudinal curvature equation of the formed part is derived. The shape of flexible roll axis controlled at a number of points is represented by the cubic spline curve and the transverse curvature of the formed part after springback is then calculated piecewise. Typically experiments for forming concave shape surface and saddle-type surface have been performed, the experiment results are measured and analyzed by a binocular stereo vision measurement system, it is demonstrated that the formed surfaces are in good agreement with the desired shapes and the presented equations are useful for the continuous forming process design.

Evaluating 3D position and velocity of subject in parabolic flight experiment by use of the binocular stereo vision measurement

A practical method for evaluating the three-dimensional (3D) position and velocity of a moving object used in the parabolic flight experiment is developed by using the binocular stereo vision measurement theory. The camera calibration mathematic model without considering the lens distortion is introduced. The direct linear transformation (DLT) algorithm is improved to accomplish the camera calibration. The camera calibration result and optimization algorithm are used to calculate the object's world coordinate from image coordinate. The 3D position and the velocity of the moving object are obtained. The standard uncertainty in estimating the velocity is 0.0024 m/s, which corresponds to 1% level of the velocity of the object in the experiment. The results show that this method is very useful for the parabolic flight experiments.

Simultaneous perimeter measurement for 3D object with a binocular stereo vision measurement system

A simultaneous measurement scheme for multiple three-dimensional (3D) objects’ surface boundary perimeters is proposed. This scheme consists of three steps. First, a binocular stereo vision measurement system with two CCD cameras is devised to obtain the two images of the detected objects’ 3D surface boundaries. Second, two geodesic active contours are applied to converge to the objects’ contour edges simultaneously in the two CCD images to perform the stereo matching. Finally, the multiple spatial contours are reconstructed using the cubic B-spline curve interpolation. The true contour length of every spatial contour is computed as the true boundary perimeter of every 3D object. An experiment on the bent surface's perimeter measurement for the four 3D objects indicates that this scheme's measurement repetition error decreases to 0.7 mm.

Precise perimeter measurement for 3D object with a binocular stereo vision measurement system

A novel measurement scheme for a three dimensional (3D) object's surface boundary perimeter is proposed. This scheme consists of three steps. First, a binocular stereo vision measurement system with two CCD cameras is devised to obtain the two images of a detected object's 3D surface boundary. Second, two B-spline active contours are applied to converge to the object's contour edges accurately in the two CCD images to perform the stereo matching. Finally, for the reconstructed 3D active contour, its true contour length is computed as the detected object's true boundary perimeter. An experiment on a bent surface's perimeter measurement indicates that this scheme's measurement repetition error decreases to 0.6%.