Active Stereo Vision System with Rotated Structured Light Patterns and Two-Step Denoising Process for Improved Spatial Resolution

Chiang, Pei-Ju; Lin, Chang-Hao

doi:10.1016/j.optlaseng.2022.106958

Cited by 13 publications

(5 citation statements)

References 16 publications

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“…Based on the characteristics of the laser surface, the spatial surface model of the laser line is represented by formula (7), which comprises six surface parameters that require solving. The least squares method is used to establish the error equation, as shown in formula (8).…”

Section: 3mentioning

confidence: 99%

“…According to the laser surface equation of formula (7) and the camera imaging model expressed by formula (12), formula ( 12) is transformed into：…”

Section: Multi-line Laser 3d Reconstruction Based On Geometric Estima...mentioning

confidence: 99%

“…Where y x ff ， are the pixel focal length of the left camera ,and 00 ( , ) uv is the coordinate of the main point of the image. By substituting formula (19) into formula (7), it get:…”

Section: Multi-line Laser 3d Reconstruction Based On Geometric Estima...mentioning

confidence: 99%

“…The authors also developed a hand tracking system to capture real-time hand movements and reconstruct them in three dimensions. PJ Chiang et al [7] researchers installed a camera and laser projector on the robot. The laser is projected on the workpiece, and by extracting the center point of the laser line and matching it with the corresponding point using the epipolar geometric relationship, the reconstruction is completed.…”

Section: Introductionmentioning

confidence: 99%

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Multi-line laser 3D reconstruction method based on spatial quadric surface and geometric estimation

huang,

Liu,

Deng

et al. 2024

Preprint

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The traditional multi-line laser 3D reconstruction is based on binocular epipolar constraints and the equation of the laser optical plane. Firstly, matching points are identified based on the epipolar constraints. Then, the correct matching points are selected based on the optical plane equation of the multi-line laser. Finally, 3D reconstruction is performed using the selected matching points. In actual production processes involving multi-line lasers, noticeable distortion occurs due to the projection of Diffractive Optical Elements (DOE) at a large angle. This results in curved laser light planes and curved reflections on the measured objects. Under such circumstances, efficiently screening matching points using the traditional method based on the laser plane equation becomes challenging. Additionally, inherent noise in multi-line laser systems introduces errors in extracted laser center coordinates, making it impossible to directly obtain high-precision 3D data solely from matching points based on epipolar line constraints. To address these issues, this paper proposes a method that utilizes spatial quadric surfaces and geometric estimation for completing multi-line laser 3D reconstructions. By analyzing the distortion principle of DOE and the positional relationship after optical diffraction, the multi-line laser manifests as a quadric surface on the optical output plane. Consequently, by calibrating the equations of the quadric surface and applying binocular polar constraints, suitable matching points for the multi-line laser can be chosen. Once an accurate matching point is identified, a minimum geometric distance estimation can be established based on the distance constraint between the point and its corresponding epipolar line. This distance represents the separation between the left and right camera's laser center points and their respective epipolar lines. Utilizing this estimate of the minimum geometric distance, a refined calculation can be performed to better satisfy epipolar constraints and obtain new matching points. Ultimately, utilizing these new matching points enables the completion of 3D reconstruction for multi-line lasers. In comparison with methods relying on spatial plane and epipolar constraints, our algorithm exhibits a superior degree of matchability and accuracy.

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Section: 3mentioning

confidence: 99%

“…According to the laser surface equation of formula (7) and the camera imaging model expressed by formula (12), formula ( 12) is transformed into：…”

Section: Multi-line Laser 3d Reconstruction Based On Geometric Estima...mentioning

confidence: 99%

“…Where y x ff ， are the pixel focal length of the left camera ,and 00 ( , ) uv is the coordinate of the main point of the image. By substituting formula (19) into formula (7), it get:…”

Section: Multi-line Laser 3d Reconstruction Based On Geometric Estima...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-line laser 3D reconstruction method based on spatial quadric surface and geometric estimation

huang,

Liu,

Deng

et al. 2024

Preprint

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show abstract

“…For temporal structured lightencoding methods, a series of pattern images are required, and the target surface is encoded at different phases along the time axis. In [8], the main commonly used methods of temporal and spatial encoding are summarized. Phase-shifting methods are a commonly used temporal-encoding projection method that projects a set of sinusoidal patterns with phase shifts to the object surface for three-dimensional reconstruction.…”

Section: Introductionmentioning

confidence: 99%

A 3D Reconstruction Method Based on Homogeneous De Bruijn-Encoded Structured Light

Li,

2024

Photonics

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Structured light three-dimensional reconstruction is one of the important methods for non-contact acquisition of sparse texture object surfaces. Variations in ambient illumination and disparities in object surface reflectance can significantly impact the fidelity of three-dimensional reconstruction, introducing considerable inaccuracies. We introduce a robust method for color speckle structured light encoding, which is based on a variant of the De Bruijn sequence, termed the Homogeneous De Bruijn Sequence. This innovative approach enhances the reliability and accuracy of structured light techniques for three-dimensional reconstruction by utilizing the distinctive characteristics of Homogeneous De Bruijn Sequences. Through a pruning process applied to the De Bruijn sequence, a structured light pattern with seven distinct color patches is generated. This approach ensures a more equitable distribution of speckle information.

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Evaluation and prediction of thermal defects in SLM-manufactured tibial components using FEM-based deep learning and statistic methods

Chung,

Zhuang,

Pan

2024

Int J Adv Manuf Technol

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Active Stereo Vision System with Rotated Structured Light Patterns and Two-Step Denoising Process for Improved Spatial Resolution

Cited by 13 publications

References 16 publications

Multi-line laser 3D reconstruction method based on spatial quadric surface and geometric estimation

Multi-line laser 3D reconstruction method based on spatial quadric surface and geometric estimation

A 3D Reconstruction Method Based on Homogeneous De Bruijn-Encoded Structured Light

Evaluation and prediction of thermal defects in SLM-manufactured tibial components using FEM-based deep learning and statistic methods

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