Robust Analysis and Laser Stripe Center Extraction for Rail Images

Gao, Huiping; Xu, Guili

doi:10.3390/app11052038

Cited by 7 publications

(4 citation statements)

References 22 publications

(26 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In most conditions, these parameters (internal, external, and aberration parameters) must be obtained experimentally and computationally. This solving process for the parameters is called camera calibration [23]. The calibration of camera parameters is a very critical aspect, and the accuracy of its calibration results and the stability of the algorithm directly affect the accuracy of the results generated by the camera.…”

Section: Camera Calibrationmentioning

confidence: 99%

“…Based on the above-mentioned studies, this paper proposes an inner diameter measurement system based on circular structured light, which can be used for the inner shaft hole of largescale workpieces, such as excavator boom. First, the center of the circular structured laser stripe is extracted based on a modified Steger method [19,20]. Second, a multi-diameter concentric calibration gauge design is used to calibrate the optical plane of the proposed system and minimize the issues of the optical plane deviation and motion error in the 1D linear stage of the the traditional calibration process.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Calibration of a circular structured light measurement system based on a multi-diameter calibrator

Zuo²,

Fan³

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

To solve the measuring problem of the inner shape of large-scale workpieces such as excavators movable arm, this paper proposes an inner shape measurement method based on circular structured light. Firstly, the center of the circular laser stripe is extracted based on a modified Steger method. Secondly, the multi-diameter concentric calibration gauge designed is used to calibrate the optical plane of the proposed system, to reduce the problem of the optical plane deviation and motion error of 1D linear stage in the traditional calibration process. Finally, the experiments are carried out and the corresponding experimental results demonstrate that the proposed measurement method not only allows for fast calibration of the camera, but also for efficient extraction of the center of the light stripe, resulting in a relative error of less than 0.012%. In addition, the measurement method will be further applied to deep-hole workpieces such as steel pipes and natural gas pipelines etc.

show abstract

Section: Camera Calibrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Calibration of a circular structured light measurement system based on a multi-diameter calibrator

Zuo²,

Fan³

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…In some cases, dynamic registration is performed during noncontact profile measurement, requiring the use of image processing algorithms and stability processing [4][5][6][7]. In other cases, post-analysis processing is conducted on the measured profile data, and the registration operation in this paper falls into this category [8][9][10][11][12][13][14][15]. There is extensive research on this topic in international literature.…”

Section: Introductionmentioning

confidence: 99%

Predicting the wear on the non-working side of the rail profile registration method and its validation

Nie,

Li,

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

Rail cross-section profile detection can assess the wear and tear of measured rails, providing crucial references for railway maintenance and upkeep. It is challenging to use the conventional method to register only the profile of rail head detection accurately. After the rail edge adjustment in some conventional railways, it becomes difficult to determine the base point of rail profile registration. Due to the wear of non-working edge of rail, a rail profile registration method is proposed. Firstly, a wear prediction model based on the generalized regression neural network is constructed by optimizing smoothing parameters through ten-fold cross-validation to achieve the optimal values. This model predicts the wear values on the non-working rail edge, providing reliable coordinates for two wear points as alignment reference points. Secondly, an initial alignment between the measured profile and the target profile is achieved using the nearest point iterative algorithm, which ensures that both profiles are in the same region and oriented similarly. Thirdly, the weight is assigned to the wear measurement points based on their respective wear values. The predicted positions of wear points are applied for calculating the translation and rotation parameters. These parameters could align the measured profile and facilitate the final profile alignment. Lastly, the experimental profiles under rail adjustment conditions were registered, verifying the accuracy of the proposed method. The research results indicate that under rail adjustment conditions, the mean squared error (MSE) between the calculated and actual values of lateral wear is 0.094 mm2, which is lower than the MSE from manual measurements. The calculated lateral wear value for experimental profiles achieved high alignment and calculation accuracy. This method can be applied in practical projects, providing an effective solution for rail head profile alignment and serving as a reference for profile alignment on the non-working rail edge with incomplete measurement data.

show abstract

“…Wang et al [9] used the difference image and region growth approach to reduce the influence of uneven background and speckle noise, then used the gray centroid approach to extract the initial center of the light stripe, which has strong robustness. Guo [10] used the brightness enhancement approach and the improved Otsu threshold segmentation approach to improve image quality. Then, use the gray centroid approach and slice fitting approach to get a robust and smooth centerline.…”

Section: Introductionmentioning

confidence: 99%

Weld line structured light stripe center extraction approach based on data dimensionality reduction

ZHENG,

LIU,

ZHU

et al. 2023

Proc. Rom. Acad. Ser. A - Math. Phys. Tech. Sci. Inf. Sci.

View full text Add to dashboard Cite

In order to improve the accuracy and speed of extracting the center of the line structured light stripe when using the vision measurement technology to get the 3D information of the weld sample, this paper proposes a center extraction approach based on the idea of data dimensionality reduction. First, use the weighted gray centroid approach to get the initial center point of the light stripe. Then, build a 7×7 template centered on the pixel block where the initial point is located and performs singular value decomposition on the 49×3 matrix within the template to get the normal direction of the initial point. Finally, calculate the stripe's exact center points through second-order Taylor expansion and smooth repair by cubic spline interpolation of breakpoints. The comparison experimental results show that this approach can effectively reduce the influence of the noise outside the light stripe on the center extraction, reduce the extraction time while ensuring the measurement accuracy, which can lay a good foundation for the point cloud data processing and surface reconstruction.

show abstract

Robust Analysis and Laser Stripe Center Extraction for Rail Images

Cited by 7 publications

References 22 publications

Calibration of a circular structured light measurement system based on a multi-diameter calibrator

Calibration of a circular structured light measurement system based on a multi-diameter calibrator

Predicting the wear on the non-working side of the rail profile registration method and its validation

Weld line structured light stripe center extraction approach based on data dimensionality reduction

Contact Info

Product

Resources

About