Shaft diameter measurement using a digital image

Sun, Qiucheng; Hou, Yuexian; Tan, Qing; Li, Chunjing

doi:10.1016/j.optlaseng.2013.11.005

Cited by 36 publications

(17 citation statements)

References 14 publications

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“…These local vision measurement methods can be classified as either bi‐dimensional or tri‐dimensional MVM methods. The former may include telecentric vision [5] and general vision [6, 7]. The latter includes structured light vision systems and stereo vision systems.…”

Section: Introductionmentioning

confidence: 99%

“…The main features of the improved method presented by Sun and co‐workers are that the geometric constraints including tangency and perpendicularity were employed and a calibration board which is fixed at a specified position was used. The accuracy of the method is relatively high and the average measurement error is about 5 μm [7]. An error correction method was introduced according to the distance from the datum plane to the camera.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Measuring straightness errors of slender shafts based on coded references and geometric constraints

Hao

Shi

Meng

et al. 2020

J. eng.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measuring straightness errors of slender shafts based on coded references and geometric constraints

Hao

Shi

Meng

et al. 2020

J. eng.

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“…The measurement methods based on machine vision have been in-depth research and rapid development in the three-dimensional measurement of mechanical parts [1][2][3]. Due to its advantages of large range, good robustness, and high precision, the measurement method based on the structured light vision has been widely developed in the parts size measurement [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Research on image enhancement of light stripe based on template matching

Liu

Bao

Zhang

et al. 2018

J Image Video Proc.

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The detection accuracy of the light stripe centers is an important factor based on the structured light vision measurement, and the quality of the light stripe images is a prerequisite for accurately detecting the light stripe centers; this paper separately proposes image enhancement methods for linear and arc light stripe images. For linear light stripes, the image with better quality is captured and the gray-scale distribution of the normal section corresponding to the light stripe centers is used as a template for light stripe images with poor quality. The poor quality light stripe images are finally optimized by linear interpolation. For arc-shaped light stripes, this paper proposes a positioning method for light stripe centers on arc, and then the gray-scale distribution of the normal cross-section of corresponding center which is on a good quality light stripe image is used as templates to improve the poor quality light quality stripe images. In order to verify the effectiveness of the light stripe image enhancement algorithms, this paper respectively presents verification methods to linear light stripe and arc light stripe. Finally, the quality of the light stripe images could be improved by image enhancement algorithms through experiments.

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“…In 2013, Sun [ 9 ] used a camera to obtain shaft diameters, employing a theory of plane geometry in the cross-section, which is perpendicular to the axis of the shaft, as shown in Figure 2 [ 9 ]. This method can achieve a high measuring accuracy, but it requires the calibration of the plane of the center line of the shaft before the measurement.…”

Section: Introductionmentioning

confidence: 99%

Shaft Diameter Measurement Using Structured Light Vision

Liu

Tan

Zhang

2015

Sensors

Self Cite

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A method for measuring shaft diameters is presented using structured light vision measurement. After calibrating a model of the structured light measurement, a virtual plane is established perpendicular to the measured shaft axis and the image of the light stripe on the shaft is projected to the virtual plane. On the virtual plane, the center of the measured shaft is determined by fitting the projected image under the geometrical constraints of the light stripe, and the shaft diameter is measured by the determined center and the projected image. Experiments evaluated the measuring accuracy of the method and the effects of some factors on the measurement are analyzed.

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Shaft diameter measurement using a digital image

Cited by 36 publications

References 14 publications

Measuring straightness errors of slender shafts based on coded references and geometric constraints

Measuring straightness errors of slender shafts based on coded references and geometric constraints

Research on image enhancement of light stripe based on template matching

Shaft Diameter Measurement Using Structured Light Vision

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