High-resolution few-pattern method for 3D optical measurement

Phase-unwrapping-free 3D reconstruction in structured light field system based on varied auxiliary point

Three-dimensional (3D) reconstruction is an essential task in structured light field (SLF) related techniques and applications. This paper presents a new method to reconstruct a 3D object point by using many auxiliary points adjacent to it. The relationship between two points in a SLF system is derived. Different from conventional "direct" methods that reconstruct 3D coordinates of the object point by using phase, slope, disparity etc., the proposed method is an "indirect" method as the 3D coordinates of auxiliary points are not needed. Based on the auxiliary point theory, the wrapped phase obtained by 4-step phase-shifting method is sufficient for 3D reconstruction, without the need for phase unwrapping. To the best of our knowledge, this is the first strategy that combines the intrinsic characteristics of structured light and light field for phase-unwrapping-free 3D reconstruction. This paper also analyzes the constraints between system architecture parameters and phase rectification, phase to depth ratio, and presents a relatively simple criterion to guide the system design. Experimental results show that, with an appropriate system architecture, the proposed method can realize accurate, unambiguous, and reliable 3D reconstruction without phase unwrapping.

High-Accuracy 3D Contour Measurement by Using the Quaternion Wavelet Transform Image Denoising Technique

In this paper, we propose an image denoising algorithm based on the quaternion wavelet transform (QWT) to address sinusoidal fringe images under strong noise in structured light 3D profilometry. The analysis of a quaternion wavelet shows that the amplitude image of the quaternion wavelet is easily affected by noise. However, the three phase images, which mainly reflect edge and texture information, are randomly and disorderly distributed with respect to noise. The QWT denoising algorithm is suitable for processing sinusoidal fringe images of complex structures in a high-accuracy 3D measurement system. Sinusoidal fringe images are collected and denoised by using the QWT algorithm and classical Gaussian smoothing (GS) denoising algorithm, and GS is used as a reference for the QWT algorithm. The results indicate that the standard deviation is reduced from 0.1448 for raw sinusoidal fringe images to 0.0192, and the signal-to-noise ratio is improved from 4.6213 dB to 13.3463 dB by using the QWT algorithm. The two algorithms have the same denoising effect for a surface with less information. For a surface with rich information, the details of the 3D contour are lost because of the image “blurring” caused by using the GS algorithm, while all edge details of the 3D contour are reconstructed by using the QWT denoising algorithm because of its characteristic of information and noise being separated from the source. For the measured face mask, the error is less than ±0.02 mm. In addition, it takes less than 20 s to run the QWT algorithm to process eight sinusoidal fringe images, which meets the requirements of high-precision measurements.

Advances and Prospects of Vision-Based 3D Shape Measurement Methods

Vision-based three-dimensional (3D) shape measurement techniques have been widely applied over the past decades in numerous applications due to their characteristics of high precision, high efficiency and non-contact. Recently, great advances in computing devices and artificial intelligence have facilitated the development of vision-based measurement technology. This paper mainly focuses on state-of-the-art vision-based methods that can perform 3D shape measurement with high precision and high resolution. Specifically, the basic principles and typical techniques of triangulation-based measurement methods as well as their advantages and limitations are elaborated, and the learning-based techniques used for 3D vision measurement are enumerated. Finally, the advances of, and the prospects for, further improvement of vision-based 3D shape measurement techniques are proposed.

Fringe-width encoded patterns for 3D surface profilometry

This paper presents a new fringe projection method for surface-shape measurement that uses novel fringe-width encoded fringe patterns. Specifically, the projection patterns are adjusted with the width of the fringe as the codeword. The wrapped phase with coding information is obtained by using the conventional wrapped phase calculation method, and the fringe order can be identified from the wrapped phase. After the fringe order is corrected based on the region growing algorithm, the fringe order and the wrapped phase can be directly used to reconstruct the surface. Static and dynamic measurements demonstrated the ability of the method to perform 3D shape measurement with only three projected patterns, single camera and projector in the least case.

Spatial-temporal phase unwrapping algorithm for fringe projection profilometry

In this paper, a generalized spatial-temporal phase unwrapping algorithm (STPUA) is proposed for extracting the absolute phase of the isolated objects with intricate surfaces. This proposed algorithm can eliminate thoroughly the order jumps of various temporal phase unwrapping algorithms (TPUAs), while inheriting the high measuring accuracy of quality-guided phase unwrapping algorithms (QGPUAs). Differing from the traditional phase unwrapping algorithms, wrapped phase is first divided into several regional wrapped phases, which can be extracted successively according to its areas and unwrapped individually by QGPUAs. Meanwhile, a series of reliable points from the fringe order map obtained from the code deformed patterns are selected to map the corresponding regional unwrapped phases into an absolute phase. The radii of selecting reliable points can provide the high measuring robustness compared with the classical point-to-point TPUAs for the complex surfaces and the motion blur, while keeping the same number of patterns. Therefore, the proposed STPUA combining SPUAs and TPUAs also can be employed in real-time three-dimensional (3D) reconstruction. Theoretical analysis and experimental results are performed to verify the effectiveness and capability of the proposed algorithm.

Self-registration shape measurement based on fringe projection and structure from motion

As an accurate and efficient shape measurement method, fringe-projection-based three-dimensional (3D) reconstruction has been extensively studied. However, patchwise point cloud registration without extra assistance is still a challenging task. We present a flexible and robust self-registration shape measurement method based on fringe projection and structure from motion (SfM). Other than ordinary structured-light measurement devices in which the camera and the projector are rigidly connected together, the camera and the projector in our method can be moved independently. An image-capturing scheme and underlying image-matching strategy are proposed. By selectively utilizing some sparse correspondence points across the fringe images as virtual markers, the global positions of the camera and the projector corresponding to each image are calculated and optimized under the framework of SfM. Dense global 3D points all over the object surface are finally calculated via forward intersection. Experimental results on different objects demonstrate that the proposed method can obtain a self-registered 3D point cloud with comparable accuracy to the state-of-the-art techniques by using only one camera and one projector, requiring no post-registration procedures and no assistant markers.

Real-time 3D shape measurement with dual-frequency composite grating and motion-induced error reduction

Phase-shifting profilometry has been increasingly sought and applied in dynamic three-dimensional (3D) shape measurement. However, the object motion will lead to extra phase shift error and thus measurement error. In this paper, a real-time 3D shape measurement method based on dual-frequency composite phase-shifting grating and motion-induced error reduction is proposed for a complex scene containing dynamic and static objects. The proposed method detects the motion region of a complex scene through the phase relations of the dual-frequency composite grating and reduces the motion-induced error with the combination of the phase calculated by a phase-shifting algorithm and the phase extracted by Fourier fringe analysis. It can correctly reconstruct the 3D shape of a complex dynamic scene and ensure high measurement accuracy of its static object as well. With the aid of the phase-shifting image ordering approach, the dynamic 3D shape of complex scenes can be reconstructed and the motion-induced error can also be suppressed in real time. Experimental results well proved that the proposed method is effective and practical.

Absolute phase measurement with four patterns based on variant shifting phases

Fringe projection profilometry has been proverbially utilized for measuring the shapes of objects. A common challenge in those systems is to accurately obtain a smooth absolute phase. Many new methods have been proposed to address this challenge. In this paper, we discuss a technique based on variant shifting phases. This approach embeds codewords into the shifting phase and only needs four patterns. However, reliable measurement results are difficult to achieve with a large number of codewords because of the phase errors. To address this shortcoming, we present a robust coding method that embeds a specific code sequence into the shifting phase and can generate more than 36 periods. The fringe order is determined using unique three-adjacent-codes combining the current period and its neighbors. An error correction algorithm is also proposed to optimize the codewords. The proposed method is experimentally verified using an established measurement system. The result shows that the proposed method is robust and efficient.