- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Methodology and implementation of a vision-oriented open CNC system for profile grinding
摘要： CNC systems with the vision function have become very valuable for intelligence machine tools because machine vision is a fast-growing intelligent feature for machines. A novel vision-oriented open CNC system was developed in this study and used in profile grinding machines for the precise machining of parts with contour surfaces, such as complex molds and cutting tools. The system is an innovation to the conventional profile grinding method and enabled the profile error to be visually detected and compensated during the machining process. In this study, a novel design methodology for a machine-vision-oriented CNC system was proposed. An Ethernet-based hardware architecture was constructed for the vision-oriented CNC system. The software characteristics of the developed CNC system were analyzed, including a new type of multi-thread software architecture, a seamless handover approach for multi-thread accessing of the memory space, the integration of the human-machine interface with image processing, and virtual-axis-based online error compensation. The running efficiency test of the software development platforms, time-consumption analysis of the measurement and control in the vision-oriented CNC system, and verification of the effectiveness of the developed vision-oriented CNC system were performed. The results indicate that the proposed vision-oriented open CNC system can effectively fuse image processing with motion control, meet the efficiency requirement, and improve the machining precision of profile grinding. The results are also valuable for developing other machine-vision-based intelligent machine tools.
关键词： Contour error,Profile grinding,Image processing,On-machine measurement,Open CNC,Machine vision
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - 3D Data Acquisition Using Stereo Camera
摘要： Computer vision systems allow digital reconstruction of targets by capturing information through remote sensors such as video cameras and scanners. In this context, the objective of this work was to evaluate the capacity and quality of three-dimensional reconstruction of static targets using the ZED stereoscopic camera. For this goal, we took images of several environments and objects with different surfaces, textures, lighting, distances and acquisition speeds. The results were compared with high-density and high precision point clouds obtained from the targets using a Leica Viva TS15 total station. The data were processed in the CloudCompare software to calculate the displacement between the models generated by the camera and the total station. Under certain circumstances, this technology is able to reconstruct three-dimensional objects and environments with an error of a few centimeters.
关键词： Machine Vision,Mesh,Point Cloud,ZED Camera,SLAM
更新于2025-09-23 15:23:52
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Face Detection and Verification Using Lensless Cameras
摘要： Camera-based face detection and verification have advanced to the point where they are ready to be integrated into myriad applications, from household appliances to Internet of Things (IoT) devices to drones. Many of these applications impose stringent constraints on the form-factor, weight, and cost of the camera package that cannot be met by current-generation lens-based imagers. Lensless imaging systems provide an increasingly promising alternative that radically changes the form-factor and reduces the weight and cost of a camera system. However, lensless imagers currently cannot offer the same image resolution and clarity of their lens-based counterparts. This paper details a first-of-its-kind evaluation of the potential and efficacy of lensless imaging systems for face detection and verification. We propose the usage of existing deep learning techniques for face detection and verification that account for the resolution, noise, and artifacts inherent in today's lensless cameras. We demonstrate that both face detection and verification can be performed with high accuracy from the images acquired from lensless cameras, which paves the way to their integration into new applications. A key component of our study is a dataset of 24,112 lensless camera images captured using FlatCam of 88 subjects in a range of different operating conditions.
关键词： coded aperture,face verification,lensless imaging,deep learning,machine vision,face detection
更新于2025-09-23 15:23:52
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Vision-Based Measurement of Dust Concentration by Image Transmission
摘要： A vision-based measurement (VBM) of dust concentration with high accuracy can be used to analyze dust pollution and reveal the distribution law of dust concentration in a production workshop. In conventional VBM, grayscale and morphological features of a dust image are commonly used. However, their measurement accuracy is limited by the atmospheric light scattering effect of surrounding light and the occlusion effect of dust particles. Thus, a high accuracy VBM system is investigated that is based on the relationship between dust concentration and image transmission (RCT) model. Meanwhile, a calculation method for image transmission that utilizes the atmospheric light scattering effect and the occlusion effect of dust particles is proposed in this paper. The experimental results show that in the proposed system, the relative error is ±3.0%, the relative uncertainty is 2.05%, the correlation is 0.99, the measurement range is 0.5–1000 mg/m3, and the measurement period is 2 s. The RCT tends to be a negative correlation, which is a quadratic polynomial. The impact of the atmospheric light scattering effect and the occlusion effect of dust particles on measurement accuracy can be eliminated by utilizing image transmission. The proposed system can be used as an alternative measurement of dust concentration in the workshop.
关键词： machine vision,global atmospheric light,Dust concentration,transmission
更新于2025-09-23 15:23:52
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Based on the Photoelectric Orientation System of the Robot in the Application of Production Line
摘要： This paper use the laser sensor to primary mapping the position of the artifacts. Then manipulator carry through accurately positioning on the artifacts by machine vision. Then the manipulator accurately capture the artifact by adjust error automatically. By using laser sensor and machine vision, the robot on industrial production line can more accurately positioning fetching artifacts and the requirements of industrial production line for precise localization of robot.
关键词： machine vision,manipulator,laser sensor
更新于2025-09-23 15:22:29
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[IEEE 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - Stuttgart, Germany (2018.11.20-2018.11.22)] 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - Camera based path planning for low quantity - high variant manufacturing with industrial robots
摘要： The acquisition costs for industrial robots have been steadily decreasing in past years. Nevertheless, they still face significant drawbacks in the required effort for the preparation of complex robot tasks which causes these systems to be rarely present so far in small and medium-sized enterprises (SME) that focus mainly on small volume, high variant manufacturing. In this paper, we propose a camera-based path planning framework that allows the fast preparation and execution of robot tasks in dynamic environments which leads to less planning overhead, fast program generation and reduced cost and hence overcomes the major impediments for the usage of industrial robots for automation in SMEs with focus on low volume and high variant manufacturing. The framework resolves existing problems in different steps. The exact position and orientation of the workpiece are determined from a 3D environment model scanned by an optical sensor. The so retrieved information is used to plan a collision-free path that meets the boundary conditions of the specific robot task. Experiments show the potential and effectiveness of the framework presented here by evaluating a case study.
关键词： high variant,low volume,Industrial robot,SME,Automatic robot programming,matching,machine vision,path planning
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Intelligent Navigation and Control of a Prototype Autonomous Underwater Vehicle for Automated Inspection of Aquaculture net pen cages
摘要： Aquaculture is one of the fastest growing food sectors worldwide providing more than 50% of world fish consumption. Towards sustainable development, aquaculture ought to design and implement technical solutions for the efficient management of farms, thus improving fish performance and decreasing operational costs, human effort and environmental impact. For this, periodic inspection of fish-cages along with early warning systems are required, functionalities that small-sized underwater vehicles can provide. In this paper, an efficient methodology for intelligent navigation of an Autonomous Underwater Vehicle (AUV) architecture is presented, yielding to a useful tool with advanced capabilities in terms of automated manipulation via real-time optical recognition approaches, miniaturization of sensors and processing units, selective monitoring, data recording/transmission operations and proper parameter calculations for further offline-analysis of captured information. The proposed AUV system constitutes an increased Technology Readiness Level version of the preliminary prototype designed earlier by our group, incorporating additional modules and application capabilities, focusing on regular periodic fish-cage net inspection in terms of net holes and fouling. The optical navigation scheme has been tested in laboratory installations under numerous scenarios so as to determine the factors affecting its robustness and efficiency. Results extracted under the validation procedure in operational conditions indicate that the proposed framework can prove a cost-effective, flexible and operative solution for aquaculture industry, enabling the transfer of operations further offshore.
关键词： remote operation,automated navigation,optical recognition,machine vision,net inspection,autonomous underwater vehicles
更新于2025-09-23 15:22:29
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A Novel Stereo Vision Measurement System Using Both Line Scan Camera and Frame Camera
摘要： In the product surface defect detection system, the detection accuracy can be greatly improved if the surface grayscale image and depth image can be adopted simultaneously. Existing 3-D cameras have the problem in precise registration of 2-D images and 3-D data, which results in inflexibility and inevitable error in practical vision tasks. Hence, we propose a novel stereo vision measurement system which is able to simultaneously acquire registered scan grayscale images and depth images without special data registration algorithm as well as the calibration method. The proposed measurement system mainly consists of a line laser system, a line scan camera, and a frame camera. The line scan camera captures clear images of objects illuminated by the line laser. In addition, the line scan camera and the frame camera form a stereo vision sensor. In this case, the line laser stripe provides location feature of the matching point for frame camera. The epipolar constraint implements the matching process between the line scan camera and the frame camera. Finally, the stereo vision measurement model is utilized to realize the 3-D coordinate reconstruction, and the z-axis coordinate is used to generate depth image. The proposed system can simultaneously obtain the image and depth information corresponding to each pixel by means of a push sweep. In the experiment, the measurement system can achieve the accuracy of 0.13 mm within a measurement range of 500 mm × 300 mm × 200 mm.
关键词： Fault diagnosis,machine vision,visual system,measurement,laser measurement applications
更新于2025-09-23 15:22:29
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Automated Visual Inspection of Glass Bottle Bottom With Saliency Detection and Template Matching
摘要： Glass bottles are widely used as containers in the food and beverage industry, especially for beer and carbonated beverages. As the key part of a glass bottle, the bottle bottom and its quality are closely related to product safety. Therefore, the bottle bottom must be inspected before the bottle is used for packaging. In this paper, an apparatus based on machine vision is designed for real-time bottle bottom inspection, and a framework for the defect detection mainly using saliency detection and template matching is presented. Following a brief description of the apparatus, our emphasis is on the image analysis. First, we locate the bottom by combining Hough circle detection with the size prior, and we divide the region of interest into three measurement regions: central panel region, annular panel region, and annular texture region. Then, a saliency detection method is proposed for finding defective areas inside the central panel region. A multiscale filtering method is adopted to search for defects in the annular panel region. For the annular texture region, we combine template matching with multiscale filtering to detect defects. Finally, the defect detection results of the three measurement regions are fused to distinguish the quality of the tested bottle bottom. The proposed defect detection framework is evaluated on bottle bottom images acquired by our designed apparatus. The experimental results demonstrate that the proposed methods achieve the best performance in comparison with many conventional methods.
关键词： multiscale filtering,machine vision,template matching,saliency detection,Defect detection
更新于2025-09-23 15:22:29
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Automatic robot path integration using three-dimensional vision and offline programming
摘要： In manufacturing industries, offline programming (OLP) platforms provide an independent methodology for robot integration using 3D model simulation away from the actual robot cell and production process, reducing integration time and costs. However, traditional OLP platforms still require prior knowledge of the workpiece position in a predefined environment, which requires complex human operations and specific-purpose designs, highly reducing the autonomy of the systems. The presented approach proposes to overcome these problems by defining a novel automated offline programming system (AOLP), which integrates a flexible and intuitive OLP platform with a state-of-the-art autonomous object pose estimation method, to achieve an environment and model independent platform for automatic robotic manufacturing. The autonomous recognition capabilities of the three-dimensional vision system provide the relative position of the workpiece model in the OLP platform, with robustness against clutter, illumination, and object material. After that, the user-friendly OLP platform allows an efficient and automatic path generation, simulation, robot code generation, and robot execution. The proposed system precision and robustness are analyzed and validated in a real-world environment on four different sets of experiment. Finally, the proposed system's features are discussed and compared with other available solutions for practical industrial manufacturing, showing the advantages of the proposed approach. Overall, despite sensor resolution limitations, the proposed system shows a remarkable precision and promising direction towards highly efficient and productive manufacturing solutions.
关键词： Machine vision,Path generation,Industrial manipulator,Automated offline programming,3D object recognition,6D pose estimation
更新于2025-09-23 15:22:29