A high performance real-time vision system for curved surface inspection

Wang, Peng; Xie, Jingming; Gu, Zhongkai; Liao, Quan; Huang, Xuanxuan

doi:10.1016/j.ijleo.2021.166514

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…To obtain the relationship between two image coordinates (u 1 ; v 1 ) and (u 2 ; v 2 ), it is necessary to eliminate the WCS in Eqs. (7) and (8). Therefore, Eq.…”

Section: Derivation Of Geometric Transformation Model For Line-scan I...mentioning

confidence: 97%

“…Fortunately, with the successful improvement and rapid diffusion of positioning systems and data processing algorithms, Global Positioning System (GPS) and Inertial Navigation System (INS) systems provide precise position and attitude observations for direct georeferencing and image rectification. 6 Currently, line-scan cameras have been widely used in motion measurements of high-speed targets 7,8 and three-dimensional (3D) scene reconstructions. 9,10 In these applications, line-scan camera calibration is an essential step.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, line-scan cameras have been widely used in motion measurements of high-speed targets 7 , 8 and three-dimensional (3D) scene reconstructions 9 , 10 . In these applications, line-scan camera calibration is an essential step.…”

Section: Introductionmentioning

confidence: 99%

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Geometric transformation modeling for line-scan images under different camera poses

Fang

Shi

et al. 2022

Opt. Eng.

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Geometrically aligning two images is a basic image process in the machine vision field. In general, the geometric transformation model is selected according to the complexity of the geometric transformation between images, and the type of camera that takes the image is ignored. However, there are essential differences in the imaging mechanism between a line-scan camera and an area array camera, so the geometric transformation model of the area array image does not conform to the geometric transformation of the line-scan image. Therefore, according to the imaging model of the line-scan camera, we established the geometric transformation model of line-scan images. A line-scan image acquisition system was built, and planar objects were imaged by different line-scan camera poses. Then, taking the proposed model as the geometric transformation model, the line-scan images collected in this paper and the line-scan images of realistic application were respectively registered. As a contrast experiment, the homography of the area array image was adopted as the geometric transformation model to align these images again. Through the comparison of registration results, the correctness of the proposed geometric transformation model of line-scan images was verified, and the accuracy of the line-scan image registration was improved.

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“…To obtain the relationship between two image coordinates (u 1 ; v 1 ) and (u 2 ; v 2 ), it is necessary to eliminate the WCS in Eqs. (7) and (8). Therefore, Eq.…”

Section: Derivation Of Geometric Transformation Model For Line-scan I...mentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Geometric transformation modeling for line-scan images under different camera poses

Fang

Shi

et al. 2022

Opt. Eng.

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The Geometric Transformation Model of Two Views Based on the Line-Scan Camera Imaging Model

Fang

Shi

Liu

et al. 2022

Intelligent Robotics and Applications

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Leveraging computer vision towards high-efficiency autonomous industrial facilities

Yousif,

Burns,

El Kalach

et al. 2024

J Intell Manuf

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Manufacturers face two opposing challenges: the escalating demand for customized products and the pressure to reduce delivery lead times. To address these expectations, manufacturers must refine their processes, to achieve highly efficient and autonomous operations. Current manufacturing equipment deployed in several facilities, while reliable and produces quality products, often lacks the ability to utilize advancements from newer technologies. Since replacing legacy equipment may be financially infeasible for many manufacturers, implementing digital transformation practices and technologies can overcome the stated deficiencies and offer cost-affordable initiatives to improve operations, increase productivity, and reduce costs. This paper explores the implementation of computer vision, as a cutting-edge, cost-effective, open-source digital transformation technology in manufacturing facilities. As a rapidly advancing technology, computer vision has the potential to transform manufacturing operations in general, and quality control in particular. The study integrates a digital twin application at the endpoint of an assembly line, effectively performing the role of a quality officer by utilizing state-of-the-art computer vision algorithms to validate end-product assembly orientation. The proposed digital twin, featuring a novel object recognition approach, efficiently classifies objects, identifies and segments errors in assembly, and schedules the paths through the data pipeline to the corresponding robot for autonomous correction. This minimizes the need for human interaction and reduces disruptions to manufacturing operations.

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A high performance real-time vision system for curved surface inspection

Cited by 5 publications

References 18 publications

Geometric transformation modeling for line-scan images under different camera poses

Geometric transformation modeling for line-scan images under different camera poses

The Geometric Transformation Model of Two Views Based on the Line-Scan Camera Imaging Model

Leveraging computer vision towards high-efficiency autonomous industrial facilities

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