Measuring Propeller Blade Width Using Binocular Stereo Vision

Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.

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.

Automatic Monitoring System for 3-D Deformation of Crustal Fault Based on Laser and Machine Vision

An automatic monitoring method of the 3-D deformation is presented for crustal fault based on laser and machine vision. The laser source and screen are independently set up in the headwall and footwall, the collimated laser beam creates a circular spot on the screen, meanwhile, the industrial camera captures the tiny deformation of the crustal fault by monitoring the change of the spot position. This method significantly reduces the cost of equipment and labor, provides daily sampling to ensure high continuity of data. A prototype of the automatic monitoring system is developed, and a repeatability test indicates that the error of spot jitter can be minimized by consecutive samples. Meanwhile, the environmental correction model is determined to ensure that environmental changes do not disturb the system. Furthermore, the automatic monitoring system has been applied at the deformation monitoring station(KJX02) of China Beishan underground research laboratory, where continuous deformation monitoring is underway.

High-precision automatic measurement of two-dimensional geometric features based on machine vision

To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.

Feature-based sequential partial vision measurement method for large scale machine parts

To realize the high-precision vision measurement for large scale machine parts, a new vision measurement method based on dimension features of sequential partial images is proposed. Instead of mosaicking the partial images, extracting the dimension features of the sequential partial images and deriving the part size according to the relationships between the sequential images is a novel method to realize the high- precision and fast measurement of machine parts. To overcome the corresponding problems arising from the relative rotation between two sequential partial images, a rectifying method based on texture features is put forward to effectively improve the processing speed. Finally, a case study is provided to demonstrate the analysis procedure and the effectiveness of the proposed method. The experiments show that the relative error is less than 0. 012% using the sequential image measurement method to gauge large scale straight-edge parts. The measurement precision meets the needs of precise measurement for sheet metal parts.

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.

A compact underwater stereo vision system for measuring fish

contributes for decisions at several production levels.However,taking length measurements is a cumbersome task that,when applied to living individuals,can induce considerable stress,increasing the risk of damage or hindering their growth.Computer vision is one of the most used non-contact tools to overcome this issue,being fast,consistent and repeatable.However,its use in aquatic environments is limited by the high cost,the difficulty of calibrating the system in underwater conditions and the complexity of implementation.This paper proposes a low-cost easy-to-use vision system that can take measurements on live fish in aquatic conditions,without the need for a special calibration or a demanding in-water calibration service.The present work implemented a compact stereo vision system and developed a method that estimates the correct length of fish,based on the variation of the angle of incidence of the light rays in the water.Given some structural conditions such as a short baseline,the system is able to measure fish with an error of less than 1%.The short baseline allows to have a compact system and reduces the effect of water refraction on the 3D reconstruction.A set of experiments were performed with real fish,working robustly for a set of orientations of the fish(even when the caudal fin and snout are on different distances to the cameras).

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.

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.

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.

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.

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.

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.

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.

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.

Light pen whole space coordinate measuring system based on a tracking turntable

Light pen coordinate measuring system(LPCMS)is a kind of portable coordinate measuring technique based on vision metrology.In classical LPCMS,the measuring range is limited to the camera’s field of view.To overcome this defect,a new LPCMS is designed in this paper to fulfil whole space coordinate measurement.The camera is installed on a turntable instead of a tripod,so that the camera can rotate to track the movement of the light pen.The new system can be applied to large scale onsite measurement,and therefore it notably extends the application of LPCMS.To guarantee the accuracy of the new system,a method to calibrate the parameters of the tracking turntable is also proposed.Fixing the light pen at a stationary position,and changing the azimuth angles of the turntable’s two shafts,so that the camera can capture the images of the light pen from different view angles.According to the invariant spatial relationship between the camera and the pedestal of the tracking turntable,a system of nonlinear equations can be established to solve the parameters of the turntable.Experimental results show that the whole space coordinate measuring accuracy of the new system can reach 0.25 mm within 10 m.It can be concluded that the newly designed system can significantly expand the measuring range of LPCMS without losing too much accuracy.

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.

Machine Vision for Non-Contact Automated Countersink Measurement

The slug rivet is widely used in wing assembly due to its longer fatigue life and better sealing performance compared with other connection technologies.As a countersink with dual-angle is widely adopted for this type of connection,the countersink diameter and depth are key factors that affect assembly quality.Therefore,it is of great importance to efficiently inspect the countersink quality to ensure high accuracy.However,contact measurements are susceptible to the loss of accuracy due to cutting debris and lube build-up,while the hole-scanning method using laser profilometry is time consuming and complex.In this paper,a non-contact method for countersink diameter and depth measurement based on a machine vision system is proposed.The countersink diameter can be directly measured by the machine vision system,while the countersink depth is determined through the countersink diameter indirectly.First,by means of image processing technology together with an improved edge detection algorithm,the countersink diameter can be obtained.Then,a 3D microscope is employed to measure the countersink depth,which helps to model the countersink.As a result,once the countersink diameter is measured,so is the depth.The experimentation demonstrated that this method has strong feasibility and enables time saving,which is conducive to improve the riveting efficiency.