The 3D reconstruction method of a line-structured light vision sensor based on composite depth images

Wang, Jiahao; Zhehai, Zhou

doi:10.1088/1361-6501/abcf64

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…Three-dimension measurement technique based on line laser has been widely used in practical industrial scenarios [1][2][3][4]. Accurate calibration results of camera parameters and light plane equation of line-structured light (LSL) are the vital basis for high precision 3D measurement [5].…”

Section: Related Workmentioning

confidence: 99%

A calibration method for line-structured light using mirror-based virtual binocular vision system

Yang

Zhang

et al. 2023

Meas. Sci. Technol.

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A calibration method for line-structured light (LSL) by using a virtual binocular vision system (VBVS) composed of one camera and a front coating plane mirror is promoted in this work. The front coating plane in the VBVS can generate much less coplanarity error in lithographic feature points and remarkably decline the imaging distortion during back coating. An encoded target is proposed to distinguish between real corners and virtual corners (mirrored corners) and achieve high-precision matching between real and virtual corners when the target is occluded during the VBVS calibration. A parameter optimization method based on 3D constraints is presented in the work to obtain accurate structural parameters and thus guarantee precise reconstruction of the LSL. Moreover, the laser stripe and its mirrored image meet the auto-epipolar constraint. Therefore, the matching between the real and virtual stripes can be realized based on the vanish point. The performance of our method is verified in the experiments.

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Section: Related Workmentioning

confidence: 99%

A calibration method for line-structured light using mirror-based virtual binocular vision system

Yang

Zhang

et al. 2023

Meas. Sci. Technol.

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“…H and V are image resolution parameters. Similarly, the crosstalk relationship of R and G channel can be expressed as equations (10) and (11), and the nomenclature of the symbols is similar to equation ( 9)…”

Section: De-crosstalk Of Color Patternsmentioning

confidence: 99%

“…Due to installation space constraints, none of the sensors were able to acquire textures. According to the LSLS technique, Wang and Zhou [10] proposed a line structured light sensor for surface reconstruction combined with composite depth images. Based on slit diffraction, four-dimensional line-scan sensors were proposed to realize the color reconstruction [11,12].…”

Section: Introductionmentioning

confidence: 99%

Surface structured light sensor with simultaneous color mapping

Yuan

Kang

Feng

et al. 2023

Meas. Sci. Technol.

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To obtain geometric information and color texture simultaneously, a surface structured light sensor consisting of a monochrome camera, a color camera, and a projector is proposed. The sensor uses a color camera to acquire surface color information while using it as a geometric measurement unit and matching with the monochrome camera to obtain geometric information. Due to the Bayer array and demosaicing algorithm of the color camera, pixel RGB components are always coupled with interference from other channels. However, existing color de-crosstalk in reconstruction is merely applied to the decoupling of color composite patterns, ignoring the intensity errors present in color fringe patterns under monochrome illumination. In our sensor, de-crosstalk of monochromatic patterns is considered to guarantee the reconstruction accuracy. The high-accuracy measurement of the sensor is validated by reconstructing standard steps, yielding a mean absolute error of 0.008 mm for distance measurements. In addition, the reconstruction experiment of a terracotta warrior verifies that the proposed sensor has potential application in the digital preservation of cultural relics.

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“…Compared with the traditional method of 3D reconstruction in vision sensors of structured line, substitution of cloud pixels into synthetic depth image is adopted by this new method, which is handy and flexible. With this method, effect of reconstruction of structured line vision sensors is improved to meet the need of 3D reconstruction in common scenes [20].…”

Section: Application Analyses Of Vision Sensors In Artistic Designmentioning

confidence: 99%

The Application of Visual Sensors in the Artistic Design of College Campus Landscape

Kan

Cao

2021

Journal of Sensors

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The research purpose is to solve the problems of low efficiency, low accuracy, and high cost of traditional environmental landscape mapping and landscape volume measurement methods in the artistic design of college campus landscape and make up the defects that the traditional campus monitoring is vulnerable to adverse weather, which results in low monitoring accuracy. Primarily, a binocular stereo vision measurement based on Scale Invariant Feature Transform (SIFT) matching algorithm is proposed, which can realize accurate collection of environmental spatial information and measurement of landscape volume without contact in the process of campus landscape design. Then, the visual monitoring system of college landscape based on the Internet of Things (IoT) is constructed to realize real-time monitoring and early warning of human damage to campus landscape. The proposed method is verified by actual measurement of different objects and simulation experiments using simulation software. Ultimately, the application of visual sensors in artistic design of college campus landscape is analysed by literature analysis. The results show that (1) the error of the improved binocular stereo vision measurement designed here is 52.32% and 59.69% lower than that of the traditional measurement method when measuring the same object with different volumes and the volumes of different objects, respectively, which indicates that the measurement accuracy of the new method is higher. (2) The proposed landscape visual monitoring method based on IoT improves the image recognition accuracy by 21% compared with the traditional digital image monitoring method. The average recognition time is shortened by 12 ms, which ensures the accuracy and improves the recognition efficiency. (3) Through the analysis of existing literature, it is found that the binocular stereo vision sensor can be used to monitor the whole process of landscape construction in real time. The sensor can be combined with social networks, mobile terminals, and physiological monitoring equipment to comprehensively analyse and evaluate people’s preference for campus landscape. The proposed method has broad application prospects in campus landscape design, construction, and maintenance. The research purpose is to provide important technical support for the improvement of the overall image of the college campus and even the city for the design of landscape environment and the technical upgrading of maintenance work in the college campus.

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The 3D reconstruction method of a line-structured light vision sensor based on composite depth images

Cited by 7 publications

References 15 publications

A calibration method for line-structured light using mirror-based virtual binocular vision system

A calibration method for line-structured light using mirror-based virtual binocular vision system

Surface structured light sensor with simultaneous color mapping

The Application of Visual Sensors in the Artistic Design of College Campus Landscape

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