Calibration of line structured light vision system based on camera’s projective center

Based on the characteristics of line structured light sensor, a speedy method for the calibration was established. With the coplanar reference target, the spacial pose between camera and optical plane can be calibrated by using of the camera’s projective center and the light’s information in the camera’s image surface. Without striction to the movement of the coplanar reference target and assistant adjustment equipment, this calibration method can be implemented. This method has been used and decreased the cost of calibration equipment, simplified the calibration procedure, improved calibration efficiency. Using experiment, the sensor can attain relative accuracy about 0.5%, which indicates the rationality and effectivity of this method.

Hybrid Visual Servoing Control for Robotic Arc Welding Based on Structured Light Vision

A novel hybrid visual servoing control method based on structured light vision is pro-posed for robotic arc welding with a general six degrees of freedom robot. It consists of a positioncontrol inner-loop in Cartesian space and two outer-loops. One is position-based visual control inCartesian space for moving in the direction of weld seam, i.e., weld seam tracking, another is image-based visual control in image space for adjustment to eliminate the errors in the process of tracking.A new Jacobian matrix from image space of the feature point on structured light stripe to Cartesianspace is provided for dierential movement of the end-e?ector. The control system model is simplifiedand its stability is discussed. An experiment of arc welding protected by gas CO2 for verifying iswell conducted.

Seam Tracking and Visual Control for Robotic Arc Welding Based on Structured Light Stereovision

A real-time arc welding robot visual control system based on a local network with a multi-level hierarchy is developed in this paper. It consists of an intelligence and human-machine interface level, a motion planning level, a motion control level and a servo control level. The last three levels form a local real-time open robot controller, which realizes motion planning and motion control of a robot. A camera calibration method based on the relative movement of the end-effector connected to a robot is proposed and a method for tracking weld seam based on the structured light stereovision is provided. Combining the parameters of the cameras and laser plane, three groups of position values in Cartesian space are obtained for each feature point in a stripe projected on the weld seam. The accurate three-dimensional position of the edge points in the weld seam can be calculated from the obtained parameters with an information fusion algorithm. By calculating the weld seam parameter from position and image data, the movement parameters of the robot used for tracking can be determined. A swing welding experiment of type V groove weld is successfully conducted, the results of which show that the system has high resolution seam tracking in real-time, and works stably and efficiently.

Effect of corneal light scatter on vision: a review of the literature

The cornea is the transparent connective tissue window at the front of the eye.The physiological role of the cornea is to conduct external light into the eye,focus it,together with the lens,onto the retina,and to provide rigidity to the entire eyeball.Therefore,good vision requires maintenance of the transparency and proper refractive shape of the cornea.The surface structures irregularities can be associated with wavefront aberrations and scattering errors.Light scattering in the human cornea causes a reduction of visual quality.In fact,the cornea must be transparent and maintain a smooth and stable curvature since it contributes to the major part of the focusing power of the eye.In most cases,a simple examination of visual acuity cannot demonstrate the reduction of visual quality secondary light scattering.In fact,clinical techniques for examining the human cornea in vivo have greatly expanded over the last few decades.The measurement of corneal back scattering qualifies the degree of corneal transparency.The measurement of corneal forward-scattering quantifies the amount of visual impairment that is produced by the alteration of transparency.The aim of this study was to review scattering in the human cornea and methods of measuring it.

Structured Light 3D Vision Based on Laser Scanning Space-encoding and Its Synchro Control

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Developing a Machine Vision System Equipped with UV Light to Predict Fish Freshness Based on Fish-Surface Color

This study assessed the feasibility of developing a machine vision system equipped with ultraviolet (UV) light, using changes in fish-surface color to predict aerobic plate count (APC, a standard freshness indicator) during storage. The APC values were tested and images of the fish surface were taken when fish were stored at room temperature. Then, images’ color-space conversion among RGB, HSV, and L*a*b* color spaces was carried out and analyzed. The results revealed that a* and b* values from the UV-light image decreased linearly during storage. A further regression analysis of these two parameters with APC value demonstrated a good exponential relationship between the a* value and the APC value (R2 = 0.97), followed by the b* (R2 = 0.85). Therefore, our results suggest that the change in color of the fish surface under UV light can be used to assess fish freshness during storage.

基于线结构光扫描的烟支表面缺陷检测方法研究

在烟支表面缺陷检测时,为解决传统二维图像方法无法获得深度信息的问题,提出一种基于线结构光传感器旋转扫描的检测方法。烟支在两同向辊轮的旋转带动下实现自转,通过线结构光视觉传感器获取物体轴向轮廓线,使用随机采样一致性拟合轮廓线,通过计算原始点到拟合轮廓的距离判断缺陷点。选取某品牌烟支在检测过程中得到的原始数据,其中多组样本的Kappa值均达到0.97,重复性达到99.3%。研究为烟支缺陷检测提供参考。

一种面向机器视觉感知的暗光图像增强网络

低光照等恶劣环境下的目标检测一直都是难点,低光照和多雾因素往往会导致图像出现可视度低、噪声大等情况,严重干扰目标检测的检测精度。针对上述问题,提出了一个面向机器视觉感知的低光图像增强网络MVP-Net,并与YOLOv3目标检测网络整合,构建了端到端的增强检测框架MVP-YOLO。MVP-Net采用了逆映射网络技术,将常规RGB图像转换为伪RAW图像特征空间,并提出了伪ISP增强网络DOISP进行图像增强。MVP-Net旨在发挥RAW图像在目标检测中的潜在优势,同时克服其在直接应用时所面临的限制。模型在多个真实场景暗光数据上取得了优于先前工作效果并且能够适应多种不同架构的检测器。其端到端检测框mAP(50%)指标达到了78.3%,比Y0L0检测器提高了1.85%。

基于线结构光的厚板焊缝特征点提取算法

针对厚板结构件在使用激光视觉系统时图像特征区域提取难和工件表面加工不均匀漫反射等导致特征点提取困难的问题,提出基于线结构光的厚板焊缝特征点提取算法。首先,激光视觉系统获取焊缝图像并使用YOLOv4算法进行预训练,利用训练获取的权重文件自动检测并获取焊缝特征感兴趣区域(ROI);其次,对ROI进行降噪、二值化等处理,通过逐行(列)搜索法得到焊缝中心线;最后,根据不同焊缝类型,基于最小二乘法使用距离法和直线段聚类的方法来提取特征点。实验结果表明:该方法可有效提取不同类型的焊缝特征点,具有鲁棒性强、识别误差小等特点。

单目三维视觉测量技术研究进展

单目三维视觉测量在视觉测量领域具有低成本、简便性、结构紧凑等优势,是以智能化、网络化制造为特征的先进制造典型技术之一。经过不断发展,单目三维视觉测量技术已成功应用于无人机导航、智能机器人、工业检测、医疗健康等领域,如今呈现出精准化、快捷化、微型化、自动化、动态化等发展趋势。以孔径数量为标准,将单目三维视觉测量技术分为单孔径及多孔径两大类,分别综述两类方法的研究现状和发展历程,重点论述了应用较广的运动恢复结构法(Structure From Motion,SFM)和光场三维测量方法,并对单目三维视觉测量技术的未来方向进行了展望。

光色周期变化对视觉疲劳影响的研究

本研究旨在探究道路照明中光色及其周期性变化对驾驶员视觉疲劳的影响。通过在高速动态条件下进行视觉特性研究,分析了综合条件下光谱光色与视觉疲劳之间的关系,并从抑制视觉疲劳的角度对光谱进行了筛选。利用闪光融合频率值对被试的视觉疲劳程度进行了量化,测试了三种不同的光色以及五组不同光色变化周期对视觉疲劳程度的影响。研究结果表明,相较于白光,蓝光光谱更具有抑制驾驶员视觉疲劳的效果;而90 s的光色变化周期对驾驶员视觉疲劳抑制效果最为显著。

翘曲板材三维重构及智能化压平的建模研究

为提高板材压平质量和效率,实现智能化压平,本文采用结构光相机获取翘曲板材点云数据,进行点云分割、点云去噪和点云精简等预处理,利用最小二乘法拟合重构了翘曲板材的三维曲面.采用微分几何的曲面理论计算得到板材的翘曲曲率,提出基于三维曲面特征的翘曲板材垫铁支点和压下点的优化方法,根据三点弯曲矫平理论得到了压力下和压下位移.翘曲板材三维轮廓的重构方法和翘曲曲率计算模型确定了垫铁位置和压下位置点优化原则,为翘曲板材智能化压平提供了理论模型.理论和实验的结果显示,重构的三维曲面与实际结果吻合,基于重构三维曲面数据计算的压平力与实测结果偏差大约为2.21%,初始平直度17.2 mm·m^(-1),压平矫直后减小为3.28 mm·m^(-1),结果准确,方法可行.

基于深度信息的照明目标识别方法

照明用电存在的能源浪费问题越来越受到关注,图像传感方法逐渐应用在照明控制领域中。基于单目图像的照明传感方法容易受到光照和纹理等因素的干扰。针对以上问题,该文提出了结合深度信息进行背景分离,提取场景中潜在的照明目标,并利用图像矩作为描述子进行目标识别的方法。搭建了双目实验平台进行室内场景测试,结果表明,该方法可以有效分离、识别并定位出场景中的照明目标,相对单目背景分离方法得到的分离轮廓更完整,对背景与目标灰度差异不敏感,对于大面积、高精度照明控制场景具备一定的应用价值。

焊缝质量离线检测技术的研究现状与发展前景

针对焊后焊缝成形缺陷存在的技术问题,对目前比较常用的几种无损检测技术,即结构光视觉检测、超声波检测、涡流检测、磁光成像检测和红外检测进行了深入研究。对上述检测方法的基本原理、系统结构、检测特点和各自的适用范围进行了讨论。研究结果表明:单种检测技术各有各的优势与短板,不能满足焊缝的全面检测要求,可以采用多种检测手段相结合的方法,实现优势互补。

从局部到全局的零参考低照度图像增强方法

为解决现有的低照度图像增强方法存在的色彩失真、细节损失以及暗区增强不足和亮区增强过度导致低照度图像增强效果不理想的问题,提出了一种从局部到全局的零参考低照度图像增强方法。采用局部照度增强对低照度图像进行像素级增强,改进了自适应光照映射估计函数,提升了照度调整能力,避免了生成大量的迭代参数,提高了模型的推理速度;采用基于Transformer结构的全局图像调整对局部增强后的图像进行全局调整,解决了亮区照度增强过度的曝光问题和暗区照度增强不足的问题,提升了图像的整体对比度;优化损失函数,对低照度图像特征和增强图像特征进行相似性约束,提升了目标检测精度。实验结果表明,LOL数据集上的客观指标峰值信噪比和结构相似性达到了20.18 dB和0.80,MIT-Adobe FiveK数据集上达到了23.31 dB和0.87,ExDark数据集上增强后图像的目标检测精度提高了7.6%,有效提升了低照度图像可视化质量和目标检测效果。

基于机器视觉的导光板漆面缺陷检测方法及实现

针对导光板在生产过程中人工检测效率低的问题,提出了一种基于机器视觉的导光板漆面缺陷检测方法。根据划痕、起泡、暗点、色差等各类典型缺陷的特点设计了对应的检测流程。改进了对比度调整算法,提出了一种以Sigmoid函数为映射曲线的自适应灰度变换方法增强起泡、划痕等点状、线状缺陷特征,采用局部自适应直方图均衡化算法突出色差缺陷轮廓,最后结合形态学处理、边缘检测等算法实现了对应缺陷的检测。实验结果表明该方法对各类点状、线性、色差缺陷的检出率达到90%。

基于激光视觉的光照变化图像分割研究

光照变化图像在分割过程中,若不能有效抑制图像中的噪声,会直接影响图像的分割精度,为提升图像的分割效果,提出基于激光视觉的光照变化图像分割方法。将图像输入至激光视觉系统中实施去噪、目标增强等处理,过程中通过该系统中的控制传感器,严密跟踪图像处理流程,提升图像的处理效果;获取图像直方图,根据直方图的平滑结果确定光照变换图像灰度直方图阈值选取范围,对图像实施区域划分获取对应的阈值,根据确定的阈值完成光照图像的精准分割。实验结果表明,使用该方法开展图像分割时,有效去除了图像噪声,分割效果较好,能够实现对图像目标的高效、准确分割。

面向遮挡感知的人体姿态估计算法研究

传统的舞台追光技术依赖于人工操作,常常难以达到设计师对追光精确性的高标准。对此,本文提出了一种基于人体位姿估计的舞台灯自动跟踪方案。目前,在舞台演出中,演员之间或与道具之间的遮挡会对姿态估计模型的准确性造成影响,进而影响追光效果的质量。为了解决演员遮挡问题,并提升人体姿态估计的准确度,本文设计了一种自顶向下的遮挡感知人体姿态估计模型和方法,该模型能显式学习人体的结构信息,采用空间注意力机制将图像特征转换为关键点特征向量,以及利用多头注意力机制增强对人体结构的学习能力,提高姿态估计在遮挡情况下的鲁棒性。此外,该模型还集成了遮挡信息的预测模块。实验表明,该方法在公开数据集上取得了优秀的表现,有效减少了在遮挡状态下的预测误差,并能判断关键点是否遭受遮挡,有望在舞台灯自动跟踪系统等复杂场景中推广应用。

基于角点校准的暗光下桥梁位移监测研究

基于机器视觉的数字图像方法监测结构物变形具有非接触性等优点,但受到暗光环境及人工标志物变形等因素的影响导致其应用受限.在现有模板匹配测量基础上,提出了暗光环境下基于Harris角点检测校准和Retinex暗光增强网络的桥梁位移监测方法和系统,以提高桥梁结构在复杂环境下的位移监测精度.进一步通过试验验证,结果显示10 m距离的暗光环境下桥梁位移监测最大绝对误差小于0.3 mm,在靶标偏转角度在0.6°至1.2°情况下,基于角点校准后的平均精度相比未校准提高了44%,说明该系统具备在暗光环境下进行工程结构位移监测的实用性.

复杂纹理工件的位姿检测方法研究

针对工业检测中一类具有平面特征的复杂纹理金属工件的位姿检测问题,使用双目视觉和DLP投影仪,将工件的局部特征作为检测重点,提出一种投影差分多线结构光的方法,使差分结构光的中心线相互补偿,减少提取光条中心线出现异常点的概率。运用极线约束特征点行对齐的特性,设计无编码双目结构光系统特征点匹配方法,提高提取平面特征点的稳定性。利用Tukey权重函数改进拟合算法,进一步提升工件被测平面拟合精度和提取工件边缘和角点的准确度,解决了传统拟合模型算法权重分配不合理的问题。经三轴精密滑台实验,并与高精度三坐标仪对比检测结果,验证该方法可以满足高精度三维测量的需求。