An absolute phase technique for 3D profile measurement using four-step structured light pattern

Xu, Jing; Liu, Shaoli; Wan, An; Gao, Bingtuan; Yi, Qiang; Zhao, Debo; Luo, Rui; Chen, Ken

doi:10.1016/j.optlaseng.2012.03.009

Cited by 29 publications

(16 citation statements)

References 12 publications

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“…Recent technical developments apply thermal infrared image (2D images) onto spatial information (3D images) to obtain 3D temperature distribution model. Three-dimensional space information can be acquired through various 3D scanning methods, such as omnidirectional vision [3], structured light technology [4,5], time-of-flight [6], and binocular vision technology [7]. Stereo vision technology can be classified into active or passive technology according to light conditions.…”

Section: Introductionmentioning

confidence: 99%

3D Temperature Distribution Model Based on Thermal Infrared Image

et al. 2017

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This paper aims to study the construction of 3D temperature distribution reconstruction system based on binocular vision technology. Initially, a traditional calibration method cannot be directly used, because the thermal infrared camera is only sensitive to temperature. Therefore, the thermal infrared camera is calibrated separately. Belief propagation algorithm is also investigated and its smooth model is improved in terms of stereo matching to optimize mismatching rate. Finally, the 3D temperature distribution model is built based on the matching of 3D point cloud and 2D thermal infrared information. Experimental results show that the method can accurately construct the 3D temperature distribution model and has strong robustness.

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Section: Introductionmentioning

confidence: 99%

3D Temperature Distribution Model Based on Thermal Infrared Image

et al. 2017

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“…Because of the higher precision and fewer fringes, the four-step phase-shifting algorithm has been widely used in practical applications [19]. It can be represented as follows:

I_{i} (x, y) = I_{0} (x, y) + I_{m} (x, y) \cos [\emptyset (x, y) + α_{i}] i = 1, 2, 3, 4

α_{1} = 0, α_{2} = p i / 2, α_{3} = p i, α_{4} = 3 p i / 2

…”

Section: Principlementioning

confidence: 99%

Full-Field Calibration of Color Camera Chromatic Aberration using Absolute Phase Maps

Liu

Huang

Zhang

et al. 2017

Sensors

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The refractive index of a lens varies for different wavelengths of light, and thus the same incident light with different wavelengths has different outgoing light. This characteristic of lenses causes images captured by a color camera to display chromatic aberration (CA), which seriously reduces image quality. Based on an analysis of the distribution of CA, a full-field calibration method based on absolute phase maps is proposed in this paper. Red, green, and blue closed sinusoidal fringe patterns are generated, consecutively displayed on an LCD (liquid crystal display), and captured by a color camera from the front viewpoint. The phase information of each color fringe is obtained using a four-step phase-shifting algorithm and optimum fringe number selection method. CA causes the unwrapped phase of the three channels to differ. These pixel deviations can be computed by comparing the unwrapped phase data of the red, blue, and green channels in polar coordinates. CA calibration is accomplished in Cartesian coordinates. The systematic errors introduced by the LCD are analyzed and corrected. Simulated results show the validity of the proposed method and experimental results demonstrate that the proposed full-field calibration method based on absolute phase maps will be useful for practical software-based CA calibration.

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“…Three-dimensional (3D) shape measurement techniques for diffuse objects have been widely used in manufacturing industries [1,2] in applications such as quality inspection and reverse engineering. Full-field fringe projection techniques [2][3][4][5][6] have been widely used to obtain the 3D shapes of these diffuse objects because they offer the advantages of noncontact operation, full-field acquisition, high accuracy, and fast, automatic data processing. Along with diffuse objects, specular surfaces also have a wide range of applications in various fields [7] , including new energy generation, illumination, and aerospace and biomedical engineering.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis and evaluation of direct phase measuring deflectometry

Zhao

Gao

Zhang

et al. 2018

Optics and Lasers in Engineering

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Three-dimensional (3D) shape measurement of specular objects plays an important role in intelligent manufacturing applications. Phase measuring deflectometry (PMD)-based methods are widely used to obtain the 3D shapes of specular surfaces because they offer the advantages of a large dynamic range, high measurement accuracy, full-field and noncontact operation, and automatic data processing. To enable measurement of specular objects with discontinuous and/or isolated surfaces, a direct PMD (DPMD) method has been developed to build a direct relationship between phase and depth. In this paper, a new virtual measurement system is presented and is used to optimize the system parameters and evaluate the system's performance in DPMD applications. Four system parameters are analyzed to obtain accurate measurement results. Experiments are performed using simulated and actual data and the results confirm the effects of these four parameters on the measurement results. Researchers can therefore select suitable system parameters for actual DPMD (including PMD) measurement systems to obtain the 3D shapes of specular objects with high accuracy.

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An absolute phase technique for 3D profile measurement using four-step structured light pattern

Cited by 29 publications

References 12 publications

3D Temperature Distribution Model Based on Thermal Infrared Image

3D Temperature Distribution Model Based on Thermal Infrared Image

Full-Field Calibration of Color Camera Chromatic Aberration using Absolute Phase Maps

Performance analysis and evaluation of direct phase measuring deflectometry

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