Robust and Accurate Surface Measurement Using Structured Light

Yang, Rongqian; Cheng, Sheng; Yang, Wei; Chen, Yazhu

doi:10.1109/tim.2007.915103

Cited by 66 publications

(15 citation statements)

References 12 publications

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“…The two cameras used in the simulation experiment have the same intrinsic parameters, the focal length is set at 16mm, the image resolution is 1280 × 1024 pixel, the pixel size is 4.8 μm × 4.8 μm, and the principal point is at the image centre. By referring to the simulation model of the orthogonal iterative algorithm [25], we uniformly select 64 points in a space of [0, 15] × [0, 15] × [0, 15] × [0, 15] making up the feature point set of the target. The feature points are divided into two groups that are projected onto the image planes of the two cameras respectively to generate imaging points, with 48 points in each group.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…In this study, at a measurement distance of 300 mm, the error is 0.05 mm, and the relative error is 0.016%. Yang et al [25] used a binocular system to capture the line structured light patterns projected by a projector, and a conicoid method is used to improve the accuracy. The relative error of this method is 0.26%.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…However, when the color or the reflection rate of the object interferes with the color of the structured light, the reconstruction precision gets affected. The sequence projection technique projects a series of patterns onto the surface of the object through a projector, including sinusoidal stripes, binary codes, and Gray codes [23,24,25]. The grayscale coding information about each point on the object surface is demodulated to obtain the corresponding projector pixel coordinates.…”

Section: Related Workmentioning

confidence: 99%

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Flexible Three-Dimensional Reconstruction via Structured-Light-Based Visual Positioning and Global Optimization

Yin

Wang

2019

Sensors

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Three-dimensional (3D) reconstruction using line structured light vision system commonly cooperates with motion restraint devices, such as parallel guide rail push-broom devices. In this study, we propose a visual positioning method to eliminate the motion constraint. An extended orthogonal iteration algorithm for visual positioning is proposed to obtain the precise position of the line structured light binocular camera system during movement. The algorithm uses the information acquired by the binocular camera, and produces a better positioning accuracy than the traditional vision localization algorithm. Furthermore, a global optimization method is proposed to calculate the poses of the camera relative to the world coordinate system at each shooting position. This algorithm effectively reduces the error accumulation and pose drift during visual positioning, and 3D information of the surface can be measured via the proposed free-moving line structured light vision system. The simulation and physical experiments performed herein validate the proposed method and demonstrate the significant improvement in the reconstruction accuracy: when the test distance is 1.5 m, the root mean square error of the point cloud is within 0.5 mm.

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Section: Experiments Resultsmentioning

confidence: 99%

Section: Experiments Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Flexible Three-Dimensional Reconstruction via Structured-Light-Based Visual Positioning and Global Optimization

Yin

Wang

2019

Sensors

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“…34,35 Based on the calibrated stereo camera, 3-D equations of the stripes from the projector can be further estimated for consistent feature matching. 36,37 This configuration can also be considered as two individual structured-light systems that are able to reduce the shadow region. 38 The use of two different focal length cameras will allow for the acquisition of dense, multiple spatial-resolution images.…”

Section: Related Calibration and Measurement Systemsmentioning

confidence: 99%

Feature enhancement for a defocusing structured-light 3-D scanning system

Liu

Lin

2018

Opt. Eng.

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Structured-light systems consisting of a camera and projector are powerful and cost-effective tools for three-dimensional (3-D) shape measurements. However, most commercial projectors are unable to generate distinct patterns due to defocusing and shallow focusing issues. We propose a hybrid method for enhancing the calibration and scanning features of the defocusing structured-light 3-D scanning system. Instead of using conventional sequential binary patterns, we replace the highest-level binary pattern by a high-order sinusoidal pattern. In our proposed system, a pan-tilt stage carrying a checkerboard is used to assist the simultaneous calibration of the camera and projector. Initially, the camera is calibrated to obtain the extrinsic positions of the stage. In addition, we utilize the multiplication of vertical and horizontal stripe patterns to enhance the corresponding features between the camera and projector. The projector is then calibrated using the extrinsic features determined from the calibrated camera. The experimental results show that the use of the high-order sinusoidal pattern significantly improves reprojection error. Our proposed method can easily be incorporated in the defocusing projector for scanning various types of objects.

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“…The gray or color-coded patterns mentioned above are sensible to ambient light and the surface color of objects. Yang et al used the light stripes and corresponding decoding method to measure the 3D surfaces [24]. However, this method is not suitable for moving objects.…”

Section: Introductionmentioning

confidence: 99%

A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light

Yao

Xue

et al. 2017

Sensors

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Depth information has been used in many fields because of its low cost and easy availability, since the Microsoft Kinect was released. However, the Kinect and Kinect-like RGB-D sensors show limited performance in certain applications and place high demands on accuracy and robustness of depth information. In this paper, we propose a depth sensing system that contains a laser projector similar to that used in the Kinect, and two infrared cameras located on both sides of the laser projector, to obtain higher spatial resolution depth information. We apply the block-matching algorithm to estimate the disparity. To improve the spatial resolution, we reduce the size of matching blocks, but smaller matching blocks generate lower matching precision. To address this problem, we combine two matching modes (binocular mode and monocular mode) in the disparity estimation process. Experimental results show that our method can obtain higher spatial resolution depth without loss of the quality of the range image, compared with the Kinect. Furthermore, our algorithm is implemented on a low-cost hardware platform, and the system can support the resolution of 1280 × 960, and up to a speed of 60 frames per second, for depth image sequences.

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Robust and Accurate Surface Measurement Using Structured Light

Cited by 66 publications

References 12 publications

Flexible Three-Dimensional Reconstruction via Structured-Light-Based Visual Positioning and Global Optimization

Flexible Three-Dimensional Reconstruction via Structured-Light-Based Visual Positioning and Global Optimization

Feature enhancement for a defocusing structured-light 3-D scanning system

A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light

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