Adaptive Binocular Fringe Dynamic Projection Method for High Dynamic Range Measurement

Yu, Changzhi; Ji, Fang; Xue, Juan; Wang, Yajun

doi:10.3390/s19184023

Cited by 21 publications

(14 citation statements)

References 37 publications

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“…Binocular camera calibration is used to characterize the relationship between the actual point of the object and the pixel points of images, which can be presented by camera parameters including camera internal parameters and camera external parameters [1][2]9]. Among various famous calibration methods, Zhang's calibration method [9] is widely used in camera calibration.…”

Section: Camera Calibrationmentioning

confidence: 99%

“…Benefiting fro m the advantages of non-contact and high precision, machine vision [1][2][3][4][5][6] has been widely used in quality detection, three-dimensional reconstruction, visual detection and other fields. The accuracy of camera calibrat ion significantly affects the precision of stereo vision measurement system [7][8][9][10], therefore, accurate camera calibration needs to be studied for reducing the measurement errors and obtaining the reliable threedimensional (3D) deformat ion fields of the object [10].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Granularity Matrix Space Model Based High Robust Multi-Ellipse Center Extraction Method for Camera Calibration

Xue

2020

IEEE Access

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Ellipse center extract ion is the important basis of camera calib ration with circle arrays calibrat ion board, wh ich direct ly affects the measurement accuracy of mach ine vision system. A iming at the problem of high noise sensitivity of the most ellipse center extract ion methods, a high robust multi-ellipse center extraction method is proposed. The idea is to transform the problem of mult i-ellipse center extraction into the problems of ellipse sub-pixel edge segmentation and edge based ellipse center clustering. Firstly, the flowchart of the proposed method is introduced. Then, the theory of fuzzy quotient space is introduced to establish the dynamic granularity matrix space model, which describes image segmentation problem as the jump ing and transformat ion of the image by hierarchical structure. Finally, an adaptive multi-ellipse sub-pixel edge segmentation method and an optimal ellipse center ext raction method are proposed based on the dynamic granularity matrix space model. Experimental results sh ow that the proposed method has higher accuracy, robustness and lower camera calibration error. INDEX TERMS multi-ellipse center, dynamic granularity matrix space, sub-pixel edge segmentation, hierarchical structure, camera calibration.

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Section: Camera Calibrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Granularity Matrix Space Model Based High Robust Multi-Ellipse Center Extraction Method for Camera Calibration

Xue

2020

IEEE Access

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“…Fringe projection profilometry (FPP) has been widely used for three-dimensional (3D) shape measurements, because of the advantages of high accuracy, large field of view (FOV) and fast measurement speed [1][2][3][4]. It uses predefined spatial intensity patterns for projection, which will be deformed relative to the original pattern due to the undulation of the surface profile.…”

Section: Introductionmentioning

confidence: 99%

Point-Wise Phase Estimation Method in Fringe Projection Profilometry under Non-Sinusoidal Distortion

Yin

Liu

Zhang

et al. 2022

Sensors

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In fringe projection profilometry, high-order harmonics information of distorted fringe will lead to errors in the phase estimation. In order to solve this problem, a point-wise phase estimation method based on a neural network (PWPE-NN) is proposed in this paper. The complex nonlinear mapping relationship between the gray values and the phase under non-sinusoidal distortion is constructed by using the simple neural network model. It establishes a novel implicit expression for phase solution without complicated measurement operations. Compared with the previous method of combining local image information, it can accurately calculate each phase value by point. The comparison results show that the traditional method is with periodic phase errors, while the proposed method can effectively eliminate phase errors caused by non-sinusoidal phase shifting.

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“…Due to the advantages of non-contact, high speed, high precision, three-dimensional (3D) shape measurement, fringe projection profilometry (FPP) [1,2,3,4] has been widely used in industrial detection, quality inspection, etc. Generally, the principle [1,2,3,4,5,6] is to project the sinusoidal and straight fringes onto the surface of the object measured, and then the camera captures the fringe images modulated by the object surface. The shape information of the object can be obtained from the absolute phase according to the phase-height mapping.…”

Section: Introductionmentioning

confidence: 99%

“…Wang [15] designed N patterns in an N-dimensional coding space to define and maximize the SNR of pattern. Afterwards, binary pattern method based binary defocusing fringe [13,14] and Gray-code [5,15] were also applied to improve the PSNR of the fringe pattern. However, the edges of binary patterns are often difficult to precisely distinguish, which reduces the measurement accuracy.…”

Section: Introductionmentioning

confidence: 99%

Fringe Phase-Shifting Field Based Fuzzy Quotient Space-Oriented Partial Differential Equations Filtering Method for Gaussian Noise-Induced Phase Error

Xue

et al. 2019

Sensors

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Traditional filtering methods only focused on improving the peak signal-to-noise ratio of the single fringe pattern, which ignore the filtering effect on phase extraction. Fringe phase-shifting field based fuzzy quotient space-oriented partial differential equations filtering method is proposed to reduce the phase error caused by Gaussian noise while filtering. First, the phase error distribution that is caused by Gaussian noise is analyzed. Furthermore, by introducing the fringe phase-shifting field and the theory of fuzzy quotient space, the modified filtering direction can be adaptively obtained, which transforms the traditional single image filtering into multi-image filtering. Finally, the improved fourth-order oriented partial differential equations with fidelity item filtering method is established. Experiments demonstrated that the proposed method achieves a higher signal-to-noise ratio and lower phase error caused by noise, while also retaining more edge details.

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Adaptive Binocular Fringe Dynamic Projection Method for High Dynamic Range Measurement

Cited by 21 publications

References 37 publications

Dynamic Granularity Matrix Space Model Based High Robust Multi-Ellipse Center Extraction Method for Camera Calibration

Dynamic Granularity Matrix Space Model Based High Robust Multi-Ellipse Center Extraction Method for Camera Calibration

Point-Wise Phase Estimation Method in Fringe Projection Profilometry under Non-Sinusoidal Distortion

Fringe Phase-Shifting Field Based Fuzzy Quotient Space-Oriented Partial Differential Equations Filtering Method for Gaussian Noise-Induced Phase Error

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