A critical review for machining positioning based on computer vision

He, Wenbin; Jiang, Zhiwen; Ming, Wuyi; Zhang, Guojun; Yuan, Jie; Yin, Ling

doi:10.1016/j.measurement.2021.109973

Cited by 23 publications

(12 citation statements)

References 68 publications

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“…It is a process mainly including taking pictures of the target object through the camera, obtaining the image of the object, using the image processor to analyze the original image, and achieving the purpose of identifying and detecting the position of the object finally, such as the position of the target, the inclination angle of the target, and so on. The functional structure of a typical machine vision alignment system is shown in Figure 15 111–113 …”

Section: Alignment Technique and Equipment For Touch Screen Laminationmentioning

confidence: 99%

“…The functional structure of a typical machine vision alignment system is shown in Figure 15. [111][112][113] The mechanical alignment technique has a simple structure and high reliability, but it can only be used in the OCA lamination process. The optical fiber alignment technique with high precision is less affected by the material.…”

Section: Machine Vision Alignment Techniquementioning

confidence: 99%

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Progress in optical adhesive and lamination process of touch screen in 3C products

et al. 2022

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Compared with the traditional keyboard and mouse input method, touch screen technique has high convenience for users. With the development of technology, touch screen is widely application in various electronic products because of their high transmittance, clear images, and convenient operation. This review mainly introduces the optical clear adhesive (OCA), liquid optical clear adhesive (LOCA), and the most commonly used LOCA ultra violet (UV)curable adhesives. Preparation and performance of UV-curable adhesives are deeply explored. The structure of touch screen, such as one glass solution (OGS), on-cell and in-cell is discussed. Moreover, lamination process includes full lamination and non-full lamination is also discussed. This review introduces the alignment technique comprise mechanical alignment technique and non-mechanical alignment technique (such as machine vision) and laminating equipment. The recent development and existing problems with the touch screen lamination process are discussed. Furthermore, this review describes the latest developments in the adhesive of touch screen lamination process and predicts possible future development trends, which could provide references for subsequent research work.

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Section: Alignment Technique and Equipment For Touch Screen Laminationmentioning

confidence: 99%

Section: Machine Vision Alignment Techniquementioning

confidence: 99%

Progress in optical adhesive and lamination process of touch screen in 3C products

et al. 2022

Self Cite

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“…Highspeed industrial quality inspection systems based on machine vision can integrate the functions of collecting target images, sending collected data, analyzing data, making judgments, executing instructions, etc., which can achieve a high degree of automation. With its advantages of fast inspection speed, high accuracy, and capability to inspect without contact [6,7], it is getting more and more attention from manufacturers and has gradually replaced manual inspection to achieve automatic inspection, which is used to distinguish between qualified and defective products with high efficiency and accuracy [8].…”

Section: Introductionmentioning

confidence: 99%

Design of Hardware Acceleration in Edge Computing Device for Bottle Cap High-Speed Inspection

Liu

Peng

et al. 2022

Wireless Communications and Mobile Computing

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High-speed product appearance inspection is crucial for modern automated industrial production such as bottle caps. The main detection method is to capture the image of bottle caps on the high-speed conveyor belt by industrial cameras and send them to the server through edge devices for various analyses. In order to improve production efficiency, it is necessary to increase the inspection rate of bottle caps. However, the transmission rate and huge data throughput of traditional inspection methods limit the inspection rate. Because of the application requirements for improving bottle cap detection efficiency, this paper proposes a hardware acceleration design based on edge devices to improve the bottle cap detection rate significantly. In this paper, an image processing module based on FPGA is designed as the edge device, improving algorithm execution speed through pipeline processing. It realizes the edge detection of the bottle cap and the fast detection of the front or back states and can send the instructions to the actuator to correct it in time when the back bottle cap is detected. It also realizes the positioning of the bottle cap area and cuts the image. Thereby, the amount of data sent to the server is significantly reduced. We have done both functional simulation and hardware implementation. Comparing with the pure software solution, the proposed design reduces the execution time of the algorithm from 16 ms to 3.07 ms, which achieves a more than four times rate increase. The amount of data that needs to be transmitted to the server per second is reduced from 7200 Kb is reduced to 25 Kb, which reduces the transmission capacity and server cache space by more than 280 times compared to the original image. In this paper, the hardware acceleration design of edge devices and the positioning and cropping of original images can greatly reduce the transmission pressure, data calculation pressure, and buffer space requirements of the central server and improve the detection rate. This design can not only be used for bottle cap inspection but also for various machine vision fields, such as defect detection of other workpieces.

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“…In addition, under the premise of ensuring the high accuracy of acquiring track plate position information, the speed at which information is obtained should be further improved to shorten the production cycle. Machine vision has become one of the most important sensing technologies for robots because of its non-contact nature and convenient ability to collect large amounts of information [7]. In recent years, the integration of robotics and vision technologies has developed rapidly.…”

Section: Introductionmentioning

confidence: 99%

“…Ni (2020) et al [12] designed a microelectronic device detection scheme, which combined the boundary tracking algorithm and template matching algorithm to localize the workpieces accurately. The Machine vision has become one of the most important sensing technologies for robots because of its non-contact nature and convenient ability to collect large amounts of information [7]. In recent years, the integration of robotics and vision technologies has developed rapidly.…”

Section: Introductionmentioning

confidence: 99%

Research on Target Localization Method of CRTS-III Slab Ballastless Track Plate Based on Machine Vision

Liu

Zheng

et al. 2021

Electronics

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In the construction of high-speed railway infrastructure, a CRTS-III slab ballastless track plate has been widely used. Anchor sealing is an essential step in the production of track plates. We design a novel automated platform based on industrial robots with vision guidance to improve the automation of a predominantly human-powered anchor sealing station. This paper proposes a precise and efficient target localization method for large and high-resolution images to obtain accurate target position information. To accurately update the robot’s work path and reduce idle waiting time, this paper proposes a low-cost and easily configurable visual localization system based on dual monocular cameras, which realizes the acquisition of track plate position information and the correction of position deviation in the robot coordinate system. We evaluate the repeatable positioning accuracy and the temporal performance of the visual localization system in a real production environment. The results show that the repeatable positioning accuracy of this localization system in the robot coordinate system can reach ±0.150 mm in the x- and y-directions and ±0.120° in the rotation angle. Moreover, this system completes two 18-megapixel image acquisitions, and the whole process takes around 570 ms to meet real production needs.

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A critical review for machining positioning based on computer vision

Cited by 23 publications

References 68 publications

Progress in optical adhesive and lamination process of touch screen in 3C products

Progress in optical adhesive and lamination process of touch screen in 3C products

Design of Hardware Acceleration in Edge Computing Device for Bottle Cap High-Speed Inspection

Research on Target Localization Method of CRTS-III Slab Ballastless Track Plate Based on Machine Vision

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