Structured Light Vision Measurement Research Articles

A three-dimensional vision measurement method based on double-line combined structured light

In this paper, a structured light vision measurement method using a scanning laser line and a positioning laser line is proposed. The novel method enables the scanning laser plane to slide along a slide rail while maintaining intersection with the positioning laser plane, eliminating the need to determine the scanning direction and moving step. During the measurement process, the laser plane equations need to be recalibrated for each new position, so a real-time calibration method is given. Initially, the geometric barycenter method is employed to detect the subpixel coordinates of the light stripe intersection point. Subsequently, these coordinates are projected into the camera coordinate system using the initial equations of the positioning laser plane. Finally, leveraging the normal information of the initial equation of the scanning laser plane and the three-dimensional coordinates of the light stripe intersection point, the real-time calibration of the scanning laser plane equations can be accomplished. The proposed method enables the three-dimensional reconstruction of objects, and its accuracy is verified through measurements on gauge blocks. Experimental results demonstrate that this method achieves precise and stable three-dimensional reconstruction of object surface shape.

An Underwater Structured Light Vision Calibration Method Considering Unknown Refractive Index Based on Aquila Optimizer

Underwater structured light vision systems have attracted the attention of researchers because of their high measurement accuracy and robustness. At present, most underwater structured light vision measurement systems consider the refractive index as a known parameter. However, the refractive index of water will change because of environmental changes such as salinity and temperature. Inaccurate refractive index will have serious influence on the measurement accuracy of the underwater structured light vision system. Therefore, an underwater structured light vision calibration method considering unknown refractive index is proposed. To avoid complex calibration process and complex solution process of a nonlinear underwater structured light vision model, a novel checkerboard usage calibration method based on Aquila Optimizer (AO) is proposed. The calibration solution process is regarded as a nonlinear optimization problem, and the optimization objective is established with the distance between the feature points intersected by the checkerboard and the laser. Finally, calibration and measurement experiments are carried out to verify the effectiveness and superiority of the proposed method.

Robot line structured light vision measurement system: light strip center extraction and system calibration

We investigate the light strip center extraction and system calibration method of a robot line structured light vision measurement system to realize fast on-line measurement of complex objects. First, the model of a robot vision measurement system is established to analyze the key technologies involved for improving the measurement accuracy of the system. Second, on the basis of the traditional gray gravity method, a gray gravity method based on the normal direction is proposed to extract the center of the laser stripe. Considering the influence of camera distortion, the accuracy of extracting the center stripe can be further improved. Third, a two-dimensional checkerboard is applied to synchronously calibrate the camera parameters, laser plane parameters, and hand-eye relationship of the robot, thus improving the efficiency and accuracy of system calibration. Finally, three-dimensional topography and the geometric dimensions of a complex part are measured by the constructed system with high accuracy. The experimental results show that the average measurement error is <0.2 mm and the measurement accuracy is <1.3 % , indicating that the system can be effectively used in actual industrial measurement.

Light plane calibration and accuracy analysis for multi-line structured light vision measurement system

This paper investigates the overall fitting accuracy of the light plane can be improved by changing the relative distance between camera and laser, altering the projection direction of the light stripe and increasing the number of extracted light stripe in the multi-line structure light measurement system. Firstly, a multi-line structured light three-dimensional measurement system platform is built, and the existing calibration plate is modified according to the requirements of the experimental design. Then, laser stripes are projected onto a blank area in the checkerboard to facilitate the extraction of the centerline of the light stripe. Moreover, the three-dimensional (3D) point cloud transformed from centerline of each stripe is used to fit into a plane by a random sample consensus algorithm (RANSAC). Finally, the influence of different experiment methods on the overall fitting accuracy of the light plane is observed. Experiments illustrate that the proposed experimental methods can reduce the relative error of the overall fitting result of the multi-line structured light plane by more than two times, and the overall calibration accuracy of the light plane is improved in terms of the error of angle between the calibrated light planes.

全景结构光视觉测量通用畸变校正模型

全景结构光视觉测量通用畸变校正模型

Research on image enhancement of light stripe based on template matching

The detection accuracy of the light stripe centers is an important factor based on the structured light vision measurement, and the quality of the light stripe images is a prerequisite for accurately detecting the light stripe centers; this paper separately proposes image enhancement methods for linear and arc light stripe images. For linear light stripes, the image with better quality is captured and the gray-scale distribution of the normal section corresponding to the light stripe centers is used as a template for light stripe images with poor quality. The poor quality light stripe images are finally optimized by linear interpolation. For arc-shaped light stripes, this paper proposes a positioning method for light stripe centers on arc, and then the gray-scale distribution of the normal cross-section of corresponding center which is on a good quality light stripe image is used as templates to improve the poor quality light quality stripe images. In order to verify the effectiveness of the light stripe image enhancement algorithms, this paper respectively presents verification methods to linear light stripe and arc light stripe. Finally, the quality of the light stripe images could be improved by image enhancement algorithms through experiments.

Shaft Diameter Measurement Using Structured Light Vision.

A method for measuring shaft diameters is presented using structured light vision measurement. After calibrating a model of the structured light measurement, a virtual plane is established perpendicular to the measured shaft axis and the image of the light stripe on the shaft is projected to the virtual plane. On the virtual plane, the center of the measured shaft is determined by fitting the projected image under the geometrical constraints of the light stripe, and the shaft diameter is measured by the determined center and the projected image. Experiments evaluated the measuring accuracy of the method and the effects of some factors on the measurement are analyzed.

Research on Calibration Method of Linear Structured Light Vision Measurement System

This template explains and demonstrates how to design a measurement system based on the size of the linear structured light vision, the system could works at realized the high precision and fast measurement of the size of mechanical parts, and accurate calibration of the system. First of all, this paper set up the experimental platform based on linear structured light vision measurement. Secondly, this paper established a system of measurement model, and puts forward a new method of calibration of structured light sensor and set up the mathematical model of sensor calibration. This calibration method only need to use some gage blocks of high precision as the target, the target position need not have a strict requirements, and the solving process will be more convenient, much easier to field use and maintenance. Finally, measuring accuracy on the system by gage blocks with high precision is verified, the experiment shows that measurement accuracy within 0.050 mmin the depth of 0-80 - mm range. This system can satisfy the demands of precision testing of most industrial parts .with its simple calibration process and high precision, it is suitable for the structured light vision calibration.

Fast phase unwrapping algorithm based on region partition for structured light vision measurement

Phase unwrapping is a key problem of phase-shifting profilometry vision measurement for complex object surface shapes. The simple path-following phase unwrapping algorithm is fast but has serious unwrapping error for complex shapes. The Goldstein+flood phase unwrapping algorithm can handle some complex shape object measurement; however, it is time consuming. We propose a fast phase unwrapping algorithm based on region partition according to a quality map of wrapped phase. In this algorithm, wrapped phase image is divided into several regions using partition thresholds, which are determined according to histogram of quality value. Each region is unwrapped by using a simple path-following phase algorithm and several groups with different priorities are generated. These groups are merged according to their priorities from high to low order and a final absolute phase is obtained. The proposed method is applied to wrapped phase images of three objects with and without noise. Experiments show that the proposed method is much faster, more accurate, and robust to noise than the Goldstein+flood algorithm in unwrapping complex phase image.

线结构光视觉测量系统运动轴线的简易标定方法

线结构光视觉测量系统运动轴线的简易标定方法