KEYWORDS: Sensors, 3D metrology, 3D scanning, Point clouds, Stereoscopy, 3D image processing, Imaging systems, Structured light, 3D acquisition, 3D modeling
In this paper, a multi-view structured light three dimensional (3D) imaging system is descried, which can perform rapid 3D reconstruction of the human body and automatically extract anthropometric data from it. This system contains 12 sets of 3D imaging sensors distributed on four pillars. Each 3D imaging sensor consists of a binocular stereo system, an Infrared laser projector and a synchronous control system based on the Field Programmable Gate Array (FPGA). The projector provides phase-shifting fringe patterns and gray code for the binocular stereo system to make 3D reconstruction. The FPGA control system enables the sensor to achieve high speed scanning. A two-step calibration method is used to calibrate the internal and external parameters of each 3D imaging sensor and external parameters between these sensors. After the 3D human body data acquisition, major body joints will be extracted as key-points. In this process, the initial location of these key-points are extracted based on a deep learning method, and then they are further corrected with local point cloud analysis. With the assistance of these key-points, the anthropometric data, such as distances (lengths, breadths, heights) and circumferences of the human body, can be calculated from its 3D data. Based on the techniques described above, the multi-view 3D imaging system can complete the whole body scanning in 2 seconds and automatically measure more than sixty dimensional data after analyzing the reconstructed 3D human data.
Fringe projection profilometry (FPP) is one of the most representative three-dimensional (3D) measurement technology. However, it is difficult to complete accurate 3D measurement with large depth variations at one time, due to the limited depth of field (DOF) of convention lenses. Addressed on this issue, we develop an autofocusing FPP system consisting of a camera with an electrically tunable lens (ETL) and a Micro-Electro-Mechanical System (MEMS) galvanometer laser scanning projector to avoid the limitation of DOF. With this system, we propose a variable focus phase-3D imaging method involving autofocusing phase retrieval and multi-focal length coefficient calibration, to achieve large DOF 3D reconstruction. Autofocus phase retrieval is based on Wiener filter deconvolution algorithm to obtain deblurring fringes under single-frame zoom exposure. To calibrate the phase mapping coefficient, We discretize the continuously variable focal into several in-focus intervals according to the phase modulation function in the measurement depth, and then perform phase-3D mapping coefficient calibration in each focusing interval to finally obtain the multi-focal length mapping coefficient. Experimental results demonstrated that the proposed method can achieve high-efficiency 3D measurement for the depth range of approximately 1,000 mm (300 mm –1300 mm) with the measurement error of 0.05%.
In this paper, a three-dimensional (3D) depth sensing system based on active structured light field imaging (ALF) is proposed. In light field imaging, one of most commonly used method for depth estimation is based on its Epipolar Plane Image (EPI), in which the slope of line features is related to parallax and is inversely proportional to the depth of the measured object. However, it is difficult to extract the line features accurately only according to the captured texture information of the object, especially in the case of weak texture, repeated texture and noise. Therefore, active phase feature provided by a phase-shifting fringe projection is introduced for this system, with which the line features in EPI can be extracted by simply searching correspondence points with the same phase value. In order to obtain depth map with measuring accuracy, a metric calibration method is proposed to establish the quantitative relationship between the slope of lines and depth. Besides that, due to the existence of distortions in the light field camera (LFC), the correspondence points in EPI cannot fit well enough with linear distribution, another calibration based on the LFC imaging model and Bundle Adjustment (BA) was implemented to correct distortions in the EPI, which can reduce the fitting errors of line features. experiment results proved that calibration method described above is effective, and the built ALF system sensor can work well for 3D depth estimation.
KEYWORDS: Calibration, 3D modeling, Imaging systems, 3D metrology, 3D image processing, Stereoscopy, Systems modeling, Microscopy, Optical metrology, Distortion
Fringe projection 3D microscopy (FP-3DM) plays an important role in micro-machining and micro-fabrication. FP-3DM may be realized with quite different arrangements and principles, which make people confused to select an appropriate one for their specific application. This paper introduces the ray-based general imaging model to describe the FP-3DM, which has the potential to get a unified expression for different system arrangements. Meanwhile the dedicated calibration procedure is also presented to realize quantitative 3D imaging. The validity and accuracy of proposed calibration approach is demonstrated with experiments.
We present a fingerprint authentication scheme based on the optical joint transform correlator (JTC) and further describe its application to the remote access control of a Network-based Remote Laboratory (NRL). It is built to share a 3D microscopy system of our realistic laboratory in Shenzhen University with the remote co-researchers in Stuttgart University. In this article, we would like to focus on the involved security issues, mainly on the verification of various remote visitors to our NRL. By making use of the JTC-based optical pattern recognition technique as well as the Personal Identification Number (PIN), we are able to achieve the aim of authentication and access control for any remote visitors. Note that only the authorized remote visitors could be guided to the Virtual Network Computer (VNC), a cross-platform software, which allows the remote visitor to access the desktop applications and visually manipulate the instruments of our NRL through the internet. Specifically to say, when a remote visitor attempts to access to our NRL, a PIN is mandatory required in advance, which is followed by fingerprint capturing and verification. Only if both the PIN and the fingerprint are correct, can one be regarded as an authorized visitor, and then he/she would get the authority to visit our NRL by the VNC. It is also worth noting that the aforementioned “two-step verification” strategy could be further applied to verify the identity levels of various remote visitors, and therefore realize the purpose of diversified visitor management.
KEYWORDS: 3D image processing, 3D metrology, Metrology, Imaging systems, Stereoscopy, Data storage, Cameras, Computer security, Computer networks, 3D image reconstruction
In this paper, the establishment of a remote laboratory for phase-aided 3D microscopic imaging and metrology is presented. Proposed remote laboratory consists of three major components, including the network-based infrastructure for remote control and data management, the identity verification scheme for user authentication and management, and the local experimental system for phase-aided 3D microscopic imaging and metrology. The virtual network computer (VNC) is introduced to remotely control the 3D microscopic imaging system. Data storage and management are handled through the open source project eSciDoc. Considering the security of remote laboratory, the fingerprint is used for authentication with an optical joint transform correlation (JTC) system. The phase-aided fringe projection 3D microscope (FP-3DM), which can be remotely controlled, is employed to achieve the 3D imaging and metrology of micro objects.
KEYWORDS: Stereoscopy, 3D image processing, Data acquisition, Fringe analysis, Phase shifting, Demodulation, Fourier transforms, 3D acquisition, Real time imaging, Structured light
A method for real-time three-dimensional (3D) imaging based on Hilbert transform is proposed. Based on the properties
of Hilbert transform and De Bruijn sequence, we design an encoding technique based on color fringe patterns to realize
3-D reconstruction of the phase distribution and range images. The calculation of phase map is implemented by using
two sinusoidal fringe patterns with phase shifting 0 and π / 2 each other. Two phase-shifted fringe patterns are assigned
to the red and blue channel of a color pattern, respectively. The phase unwrapping is accomplished with aid of the De
Bruijn sequence pattern stored in the green channel. The experiment results show that the proposed method can not only
acquire 3D data in real-time and one-shot fashion, but also obtain high-resolution and high-density range image data
without any error propagation.
KEYWORDS: Gaussian filters, Computer simulations, Detection and tracking algorithms, Machine vision, Edge detection, Image filtering, Digital image processing, 3D modeling, Signal to noise ratio, Optoelectronics
Circular target is one of the most commonly used artificial markers in machine vision. An alternative method for center location of circular targets with sub-pixel accuracy based on surface fitting is presented in this paper. The gray level distribution around the image of the circular target is modeled starting form one-dimensional step edge smoothed with Gaussian filter, and then extending to two-dimensional case by means of variable substitution of the elliptical rotation. The surface model aforementioned is a non-elementary function, so an approximate expression is found subsequently to make the numerical computation executable. The parameters of the surface model are estimated with algebraic least square fitting, from which the accurate center location can be calculated. The experiment results show the proposed method is more robust to image degradation comparing with the most commonly used method.
In this paper, a design of demodulation system applied to Fiber Bragg Grating sensor will be illustrated. This system is
based on the principle of Fiber Bragg Grating strain sensing; therefore this applied system has the following
characteristics: high sensitivity, high precision, low cost and so on.
Demodulation system bases on the traditional matching method, and uses the two matched Fiber Bragg Grating parallel
mode. Just because of this, it improves on a certain extent compared with the traditional one. The two Fiber Bragg
Gratings are pasted on Hollow Aluminum Cantilever respectively so as to realize the high precision and the large scale
strain demodulation.
This paper proves the following theory through the academic analyses and experimentation, that is: pasting Fiber Bragg
Grating on Hollow Aluminum Cantilever can improve the response sensitivity. During the process of matching,
increasing the load on the Hollow Aluminum Cantilever, when the qualities of load cannot beyond the limited quality,
there is a good linearity relation between the change of load's quality and the change of wavelength. The limited quality
comes from the experimentation. The experimentation proves that the structure of two matched Fiber Bragg Grating
parallel can increase the range of strain which can be measured largely, and at the same time this structure can solve
double-value problem which exists in the ordinary matching method. The strain sense signal through the two parallel
demodulation Fiber Bragg Gratings into data processing circuit. The single chip processes the data from the data
processing circuit and works out the strain which is detected by Fiber Bragg Grating sensor.
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