FPGA and computer-vision-based atom tracking technology for scanning probe microscopy

Atom tracking technology enhanced with innovative algorithms has been implemented in this study,utilizing a comprehensive suite of controllers and software independently developed domestically.Leveraging an on-board field-programmable gate array(FPGA)with a core frequency of 100 MHz,our system facilitates reading and writing operations across 16 channels,performing discrete incremental proportional-integral-derivative(PID)calculations within 3.4 microseconds.Building upon this foundation,gradient and extremum algorithms are further integrated,incorporating circular and spiral scanning modes with a horizontal movement accuracy of 0.38 pm.This integration enhances the real-time performance and significantly increases the accuracy of atom tracking.Atom tracking achieves an equivalent precision of at least 142 pm on a highly oriented pyrolytic graphite(HOPG)surface under room temperature atmospheric conditions.Through applying computer vision and image processing algorithms,atom tracking can be used when scanning a large area.The techniques primarily consist of two algorithms:the region of interest(ROI)-based feature matching algorithm,which achieves 97.92%accuracy,and the feature description-based matching algorithm,with an impressive 99.99%accuracy.Both implementation approaches have been tested for scanner drift measurements,and these technologies are scalable and applicable in various domains of scanning probe microscopy with broad application prospects in the field of nanoengineering.

Accurate Measurement Method for Tube's Endpoints Based on Machine Vision

Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube＇s endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube＇s endpoints based on machine vision is proposed. First, reflected light on tube＇s surface can be removed by using photometric linearization. Then, based on the optimization model for the tube＇s endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube＇s endpoint are obtained. To confirm the feasibility, ll tubes are processed to remove the reflected light and then the endpoint＇s positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 ram. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube＇s endpoints without any surface treatment or any tools and can realize on line measurement.

Machine Vision Based Measurement of Dynamic Contact Angles in Microchannel Flows

When characterizing flows in miniaturized channels, the determination of the dynamic contact angle is important. By measuring the dynamic contact angle, the flow properties of the flowing liquid and the effect of material properties on the flow can be characterized. A machine vision based system to measure the contact angle of front or rear menisci of a moving liquid plug is described in this article. In this research, transparent flow channels fabricated on thermoplastic polymer and sealed with an adhesive tape are used. The transparency of the channels enables image based monitoring and measurement of flow variables, including the dynamic contact angle. It is shown that the dynamic angle can be measured from a liquid flow in a channel using the image based measurement system. An image processing algorithm has been developed in a MATLAB environment. Images are taken using a CCD camera and the channels are illuminated using a custom made ring light. Two fitting methods, a circle and two parabolas, are experimented and the results are compared in the measurement of the dynamic contact angles.

Spectral Test Instrument for Color Vision Measurement

Common displays such as CRT or LCD screens have limited capabilities in displaying most color spectra correctly. The main disadvantage of these devices is that they work with three primaries and the colors displayed are the mixture of these three colours. Consequently these devices can be confusing in testing human color identification, because the spectral distribution of the colors displayed is the combined spectrum of the three primaries. We have developed a new instrument for spectrally correct color vision measurement. This instrument uses light emitting diodes (LEDs) and is capable of producing all spectra of perceivable colors, thus with appropriate test methods this instrument can be a reliable and useful tool in test~ing human color vision and in verifying color vision correction.

Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part

In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine（CMM）.Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error（RMSE） of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.

Single Camera 3-D Coordinate Measuring System Based on Optical Probe Imaging

A new vision coordinate measuring system--single camera 3 D coordinate measuring system based on optical probe imaging is presented. A new idea in vision coordinate measurement is proposed. A linear model is deduced which can distinguish six freedom degrees of optical probe to realize coordinate measurement of the object surface. The effects of some factors on the resolution of the system are analyzed. The simulating experiments have shown that the system model is available.

STUDY ON MEASUREMENT OF WOOD SURFACEROUGHNESS BY COMPUTER VISION

The working processes, machining devices and tools, cutting amount, consumption of materials, productivity and quality of products are directly affected by wood surface roughness. This paper gives an extensive review of methods used previously to measure wood surface roughness, and concludes that computer vision is the most suitable technique. The preliminary study shows that computer vision method has the advantages of a noncontact, three-dimensional measurement, high speed and well correlates with stylus tracing method. This method can be used in classification and in-time measurement of wood surface roughness after being improved.

Accuracy of Measuring Camera Position by Marker Observation

A lower bound to errors of measuring object position is constructed as a function of parameters of a monocular computer vision system (CVS) as well as of observation conditions and a shape of an observed marker. This bound justifies the specification of the CVS parameters and allows us to formulate constraints for an object trajectory based on required measurement accuracy. For making the measurement, the boundaries of marker image are used.

Accurate vision measurement for kinematic parameters of satellite separation tests

The accurate measurement of kinematic parameters in satellite separation tests has great significance in evaluating separation performance. A novel study is made on the measuring accuracy of monocular and binocular, which are the two main vision measurement methods used for kinematic parameters. As satellite separation process is transient and high-dynamic, it will bring more extraction errors to the binocular. Based on the design approach of intersection measure and variance ratio, the monocular method reflects higher precision, simpler structure and easier calibration for level satellite separation. In ground separation tests, a high-speed monocular system is developed to gain and analyze twelve kinematic parameters of a small satellite. Research shows that this monocular method can be widely applied for its high precision, with position accuracy of 0.5 mm, speed accuracy of 5 mm/s, and angular velocity accuracy of 1 (°)/s.

VISION-BASED MEASUREMENT OF FREE-FORM SURFACES

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An image mosaic technique with non-overlapping regions based on microscopic vision in precision assembly

Microscopic vision has been widely applied in precision assembly.To achieve sufficiently high resolution in measurements for precision assembly when the sizes of the parts involved exceed the field of view of the vision system,an image mosaic technique must be used.In this paper,a method for constructing an image mosaic with non-overlapping areas with enhanced efficiency is proposed.First,an image mosaic model for the part is created using a geometric model of the measurement system installed on a X-Y-Z precision stages with high repeatability,and a path for image acquisition is established.Second,images are captured along the same path for a specified calibration plate,and an entire image is formed based on the given model.The measurement results obtained from the specified calibration plate are utilized to identify mosaic errors and apply compensation for the part requiring measurement.Experimental results show that the maximum error is less than 4μm for a camera with pixel equivalent 2.46μm,thereby demonstrating the accuracy of the proposed method.This image mosaic technique with non-overlapping regions can simplify image acquisition and reduce the workload involved in constructing an image mosaic.

U-shaped Vision Transformer and Its Application in Gear Pitting Measurement

Although convolutional neural networks have become the mainstream segmentation model,the locality of convolution makes them cannot well learn global and long-range semantic information.To further improve the performance of segmentation models,we propose U-shaped vision Transformer(UsViT),a model based on Transformer and convolution.Specifically,residual Transformer blocks are designed in the encoder of UsViT,which take advantages of residual network and Transformer backbone at the same time.What is more,transpositions in each Transformer layer achieve the information interaction between spatial locations and feature channels,enhancing the capability of feature learning.In the decoder,for enhancing receptive field,different dilation rates are introduced to each convolutional layer.In addition,residual connections are applied to make the information propagation smoother when training the model.We first verify the superiority of UsViT on automatic portrait matting public dataset,which achieves 90.43%accuracy(Acc),95.56%Dice similarity coefficient,and 94.66%Intersection over Union with relatively fewer parameters.Finally,UsViT is applied to gear pitting measurement in gear contact fatigue test,and the comparative results indicate that UsViT can improve the Acc of pitting detection.

Recognition of Multifunctional Coded Target in Single-camera Mobile 3D-vision Coordination Measurement

Single-camera mobile-vision coordinate measurement is one of the primary methods of 3D-coordinate vision measurement, and coded target plays an important role in this system. A multifunctional coded target and its recognition algorithm is developed, which can realize automatic match of feature points, calculation of camera initial exterior orientation and space scale factor constraint in measurement system. The uniqueness and scalability of coding are guaranteed by the rational arrangement of code bits. The recognition of coded targets is realized by cross-ratio invariance restriction, space coordinates transform of feature points based on spacial pose estimation algorithm, recognition of code bits and computation of coding values. The experiment results demonstrate the uniqueness of the coding form and the reliability of recognition.

Up-Sampled Cross-Correlation Based Object Tracking & Vibration Measurement in Agriculture Tractor System

This research introduces a challenge in integrating and cleaning the data,which is a crucial task in object matching.While the object is detected and then measured,the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage,abnormal stopping,and disaster.Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement.To solve all these problems,this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to a predetermined portion of the image.A novel white color sticker of the known dimensions marked with a color dot is pasted on the surface of an object for the best result in the template matching using the Improved Up-Sampled Cross-Correlation(UCC)algorithm.The vibration measurement is calculated using the Finite-Difference Algorithm(FDA),a machine vision systemfitted with a macro lens sensor that is capable of capturing the image at a closer range,which does not affect the quality of displacement measurement from the video frames.Thefield test was conducted on the TAFE(Tractors and Farm Equipment Limited)tractor parts,and the percentage of error was recorded between 30%and 50%at very low vibration values close to zero,whereas it was recorded between 5%and 10%error in most high-accelerations,the essential range for vibration analysis.Finally,the suggested system is more suitable for measuring the vibration of stationary machinery having low frequency ranges.The use of a macro lens enables to capture of image frames at very close-ups.A 30%to 50%error percentage has been reported when the vibration amplitude is very small.Therefore,this study is not suitable for Nano vibration analysis.

基于机器视觉的木窗双端铣削加工尺寸测量方法

木窗是一种以木材或木质复合材料为主要构件的门窗产品,具有良好的生态性能和美观效果,适用于多种建筑形式和风格,其中木窗尺寸是衡量木窗加工是否合格的重要指标。对于传统木窗双端铣削加工中人工测量尺寸方式存在的精度低、效率低等问题,提出一种基于机器视觉的木窗双端铣削加工尺寸测量方法,以期提高尺寸测量精度及加工效率。该方法针对木窗厚度引起的透视效应,提出一种物平面提升法,以消除透视投影带来的误差。首先对木窗图像采取灰度化、平滑去噪、图像增强及轮廓分割等举措,完成图像预处理,提取出木窗内外轮廓区域。对轮廓区域应用Canny算子获取木窗像素级轮廓。通过优化的Zernike矩亚像素边缘提取算法对木窗像素级边缘进行更精确的定位,得到亚像素级轮廓坐标。通过最小二乘法联合RANSAC算法对亚像素轮廓坐标进行拟合,得到拟合轮廓及角点坐标,并使用透视矫正模型计算出木窗尺寸。实验利用3种厚度规格相同但尺寸不同的松木材质矩形木窗,分别测量其内框和外框的边框尺寸及对角线尺寸,并与对应的实际物理尺寸对比,验证了所提木窗尺寸测量方法的检测精度。研究结果表明,所提方法与实际物理尺寸值相比,其绝对误差范围在±0.12 mm之内,相对误差在±0.1%之内,且效率及精度高,可以满足对木窗的在线尺寸检测。

基于低空视觉的直升机旋翼轴心轨迹测量法

为满足直升机飞行状态旋翼轴心轨迹测量需求,提出了一种基于低空双目视觉的轴心轨迹测量方法。首先,针对高速旋转体的小量测量,基于立体视觉测量原理设计构建了以无人机为低空移动平台的旋翼轴心轨迹视觉测量系统。其次,针对动-动测量环境条件,提出了地面标定与空中动态实时标定联合的测量系统标定方法。然后,基于空间几何关系,论述了旋翼轴心静态估计与动态轨迹测量方法;最后,进行了测量系统地面精度验证试验与直升机地面开车状态的旋翼轴心轨迹测量试验。试验结果表明,该方法准确可靠,点间距离精度优于1‰,可实现轴心轨迹的非接触精确测量,还可推广应用于其他动态小量测量任务。

电力变压器关键尺寸视觉检测方法及其缩比模型验证

电力变压器的关键尺寸测量是其装配制造、运输安装过程中重要一环,现有测量方法操作繁琐且效率较低。为此,本文提出了一种适用于110 kV油浸式电力变压器关键尺寸视觉检测方法,该方法利用YOLO目标检测算法、Grabcut图像分割算法实现关键组部件的智能检测与分割,然后基于双目立体视觉原理实现套管相间距离及变压器最大截面外形尺寸等关键尺寸的测量。本文搭建了110 kV油浸式电力变压器外观缩比模型,试验分析了拍摄距离和角度等因素对电力变压器关键尺寸视觉检测的影响。结果表明,本文基于缩比模型试验实现了在不同拍摄距离与角度下变压器关键尺寸的视觉检测,验证了该方法的有效性。本文方法可以为110 kV油浸式电力变压器现场尺寸测量提供参考。

异常点云干扰下的车身构件鲁棒性配准方法

点云配准是大型车身构件位姿参数测量的关键方法,但现有算法在大量异常点云干扰下难以配准至有效位姿,从而导致匹配失真,进而无法保证后续机器人作业质量。针对此问题,提出一种能够有效抑制异常点云干扰的车身构件鲁棒性配准算法——鲁棒函数加权方差最小化(RFWVM)算法。建立鲁棒函数加权目标函数,通过施加随迭代次数可变的动态权重来抑制配准过程中异常点云的影响,并由高斯-牛顿法迭代完成刚性转换矩阵的求解。以高铁白车身侧墙、汽车车门框为研究对象的试验结果表明,较经典的最近点迭代(ICP)算法、方差最小化(VMM)算法、加权正负余量方差最小化(WPMAVM)算法和去伪加权方差最小化(DPWVM)算法,所提出的RFWVM算法配准精度更高,能够有效抑制各种异常点云对配准结果的影响,并具有更好的稳定性和鲁棒性,能够有效实现各类车身构件点云的精确配准。

二维主动位姿引导的单目空间姿态测量方法

针对空间物体姿态快速测量问题,以构建视觉最小系统需求为依据,研究了一种基于二维主动位姿引导的单目视觉空间姿态测量方法,建立了单目相机、二维载台与倾角仪之间的姿态测量模型,实现了空间物体的姿态角的测量。该方法以大地倾角仪坐标系统一测量系统的测量基准,由精密二维载台引导单目相机覆盖地空大视野三维空间,通过前期标定设计完成了单目相机与二维载台之间的工装校准;建立了载台坐标系、摄像机坐标系以及大地倾角仪坐标系之间的姿态测量传递模型,实现了定轴旋转双视角拍照下的空间物体的姿态解算和角度测量。构建了实验验证环境,测角实验结果表明:在系统测量基准坐标系下,其俯仰角的测量误差≤0.82°,测量相对误差≤6.1%;其横滚角的测量误差≤0.43°,测量相对误差≤3.4%。

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。