Enhancing the accuracy of forging measurement using silhouettes in images

Hurník, Jakub; Zatočilová, Aneta; Koutný, Daniel; Paloušek, David

doi:10.1016/j.measurement.2022.111059

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…Since the use of the traditional operators cannot have accurate profile extraction, researchers have come up with various novel ways for the image enhancement. [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] Among them, mathematical method has been intensively used for image enhancement. One good example is shown in the application of the Hausdorff derivative, which is used for image edge extraction.…”

Section: Introductionmentioning

confidence: 99%

“…[12] The other research efforts for acquiring the image enhancement involved with the method of using wavelets. [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] The wavelets are generally wave-like oscillatory functions. They show a recovery impact since the features acquired via the wavelets show different resolutions.…”

Section: Introductionmentioning

confidence: 99%

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Image Enhancement via Special Functions and Its Application for Near Infrared Imaging

et al. 2023

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Image enhancement is important given that it can be used to highlight the area of interest in the images. This article designs four filters via special function for realizing image enhancement. Firstly, a filter based on the exponential function is designed. When the value of the progression is even, the edge feature can be extracted. When the value of the progression is odd, sharp contrast can be obtained. Secondly, a filter is built using hyperbolic cosine and its inverse function, where a printmaking feature can be extracted. Thirdly, a filter is made via a hyperbolic secant function and its inverse. It can lead to the extraction of image edge. When the progression value is increasing, marginal effect can be found and the brightness is decreasing. Ripple morphology can be found. Fourthly, a filter is constructed through a hyperbolic sine function and its inverse, where marginal features can be extracted. Furthermore, these filters are useful for extracting the marginal features even when a high noise density of 0.9 is added to the original images. They are useful for highlighting the images acquired from near infrared imaging.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Image Enhancement via Special Functions and Its Application for Near Infrared Imaging

et al. 2023

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“…The last technology is passive close-range photogrammetry. This includes the measurement of forgings based on their silhouettes [31][32][33][34][35][36] , and passive stereo vision 37,38 . The first mentioned method showed advantages for in-process measurement of axis-straightness and cross-section of heavy forgings of basic shapes, for which this method is limited.…”

Section: Introductionmentioning

confidence: 99%

Forging measurement using passive stereo vision

Vítek,

Hurník,

Vaverka

et al. 2023

Optical Measurement Systems for Industrial Inspection XIII

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Dimensional inspection during manufacturing of high-temperature forging workpieces is still an unsolved research topic. In this work, an approach to reconstruct the hot forging surface using passive stereovision was proposed. The challenges are the irregular thermal radiation of the forging in the visible spectrum, which is affected by scales, heat haze, and an unstable environment. Unlike the approaches presented in the literature, we use the radiated light, without an external light source. High dynamic resolution images were used to image the forging surface with highly varying brightness. The effect of optical filtering on the contrast of the fine surface structure was investigated and evaluated by spectral analysis of the images, with the best results obtained in the green spectrum. A comparison of feature detectors was performed for the specific surface structure of the hot forging. The best results in terms of density of reconstructed points were obtained using the KAZE method. The final verification of the achievable accuracy was performed in a measurement volume of approx. 500×400×350 mm. An 877 °C hot steel pipe sample was measured with a single point standard deviation error of 0.28 mm, which is an order of magnitude higher than under ideal conditions, but acceptable in comparison with manufacturing tolerances. Further developments could be related to the application of dense image matching, further investigation of interfering effects, and application of the proposed methods in the industrial environment.

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“…Zhou et al [17] proposed a vision measurement method for large forgings based on feature line reconstruction, the average gray scale method was used to adjust the image under high temperature. Hurník et al [18] proposed the cylindrical forging dimensions measurement system based on the contour extraction method, the weighted filter was used to eliminate the image noise interference in the industrial environment, and the red bandpass filter was used to improve the contrast of the forging image. The diameter measurement error of the measurement system was ±1 mm.…”

Section: Introductionmentioning

confidence: 99%

The real-time vision measurement of multi geometric information of the rolled ring in the hot ring rolling process based on deep learning

Huang,

Wang,

Dong

et al. 2023

Meas. Sci. Technol.

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Hot ring rolling (HRR) is an advanced incremental metal-forming technology to manufacture high-performance rings. Nowadays, the mechanical or laser-sensors measurement methods can only obtain one value of the dimensions on the ring circumference per time unit, the measurement data is single and the information is limited. This paper presents a real-time vision measurement method for multi geometric information of the rolled ring such as ring’s diameter, center position, circularity and growth speed in HRR process. Firstly, the deep learning model is constructed to intelligently and quickly identify rolled ring targets from complex image backgrounds, then the adaptive linear gray scale transformation algorithm is proposed to adjust the gray scale contrast of the image according to changes in ring temperature, the interference of oxide scales and flying chips are eliminated by morphology operation. Finally, the least square method is used to fit the contour points, and further the rolled ring’s geometric information and corresponding variation trend are calculated. Several experiments are conducted on a vertical HRR mill, the geometric information of the rolled ring during the HRR is measured in real-time under the interference of harsh working conditions. For the ring with outer diameter of 350 mm, the measurement error of ring’s outer and inner diameter is less than 0.8 mm, the average processing time per image takes about 80 ms. The research provides a basis for accurate measurement of HRR process.

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Enhancing the accuracy of forging measurement using silhouettes in images

Cited by 8 publications

References 37 publications

Image Enhancement via Special Functions and Its Application for Near Infrared Imaging

Image Enhancement via Special Functions and Its Application for Near Infrared Imaging

Forging measurement using passive stereo vision

The real-time vision measurement of multi geometric information of the rolled ring in the hot ring rolling process based on deep learning

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