Generalized phase unwrapping method that avoids jump errors for fringe projection profilometry

Phase correction strategy based on structured light fringe projection profilometry

Fringe projection profilometry based on structured light has been widely used in 3-D vision due to its advantages of simple structure, good robustness, and high speed. The principle of this technique is to project multiple orders of stripes on the object, and the camera captures the deformed stripe map. Phase unwrapping and depth map calculation are important steps. Still, in actual situations, phase ambiguity is prone to occur at the edges of the object. In this paper, an adaptive phase segmentation and correction (APSC) method after phase unwrapping is proposed. In order to effectively distinguish the stable area and unstable area of the phase, a boundary identification method is proposed to obtain the structural mask of the phase. A phase compensation method is proposed to improve the phase accuracy. Finally, we obtain the 3-D reconstruction result based on the corrected phase. Specific experimental results verify the feasibility and effectiveness of this method.

Nonlinear phase error correction method based on multi-grayscale coding

Fringe projection profilometry is a non-contact and highly efficient 3D measurement technique widely used in various applications. However, the nonlinear intensity response of digital projectors affects measurement accuracy. While increasing the number of fringe projections can reduce the errors caused by nonlinear problems, it significantly prolongs the measurement time. In order to improve both accuracy and speed simultaneously, a nonlinear phase error correction method based on multi-grayscale coding is proposed. The intensity response curve of the system is fitted by the grayscale images, and then the grayscale values of the phase-shifting fringe images are corrected to reduce the nonlinear error. In order to reduce the number of fringe projections and speed up the measurement, the multi-grayscale coding method is used to divide the phase interval by the order of the gray values of the same pixel in multiple grayscale images. The experimental results validate the efficacy of the proposed multi-grayscale coding method. An accurate phase calculation is achieved, and a single reconstruction can be achieved with only seven photos. After the nonlinear correction, the phase accuracy of the three-step phase-shifting algorithm is increased by 50.77%, and the reconstruction accuracy of the standard ball is increased by 46.38%.

Phase Unwrapping Error Correction Based on Multiple Linear Regression Analysis

Fringe projection profilometry (FPP) is prone to phase unwrapping error (PUE) due to phase noise and measurement conditions. Most of the existing PUE-correction methods detect and correct PUE on a pixel-by-pixel or partitioned block basis and do not make full use of the correlation of all information in the unwrapped phase map. In this study, a new method for detecting and correcting PUE is proposed. First, according to the low rank of the unwrapped phase map, multiple linear regression analysis is used to obtain the regression plane of the unwrapped phase, and thick PUE positions are marked on the basis of the tolerance set according to the regression plane. Then, an improved median filter is used to mark random PUE positions and finally correct marked PUE. Experimental results show that the proposed method is effective and robust. In addition, this method is progressive in the treatment of highly abrupt or discontinuous regions.

FPP-SLAM: indoor simultaneous localization and mapping based on fringe projection profilometry

Simultaneous localization and mapping (SLAM) plays an important role in autonomous driving, indoor robotics and AR/VR. Outdoor SLAM has been widely used with the assistance of LiDAR and Global Navigation Satellite System (GNSS). However, for indoor applications, the commonly used LiDAR sensor does not satisfy the accuracy requirement and the GNSS signals are blocked. Thus, an accurate and reliable 3D sensor and suited SLAM algorithms are required for indoor SLAM. One of the most promising 3D perceiving techniques, fringe projection profilometry (FPP), shows great potential but does not prevail in indoor SLAM. In this paper, we first introduce FPP to indoor SLAM, and accordingly propose suited SLAM algorithms, thus enabling a new FPP-SLAM. The proposed FPP-SLAM can achieve millimeter-level and real-time mapping and localization without any expensive equipment assistance. The performance is evaluated in both simulated controlled and real room-sized scenes. The experimental results demonstrate that our method outperforms other state-of-the-art methods in terms of efficiency and accuracy. We believe this method paves the way for FPP in indoor SLAM applications.

Time-overlapping structured-light projection: high performance on 3D shape measurement for complex dynamic scenes

High-speed three-dimensional (3D) shape measurement has been continuously researched due to the demand for analyzing dynamic behavior in transient scenes. In this work, a time-overlapping structured-light 3D shape measuring technique is proposed to realize high-speed and high-performance measurement on complex dynamic scenes. Time-overlapping structured-light projection is presented to maximumly reduce the information redundancy in temporal sequences and improve the measuring efficiency; generalized tripartite phase unwrapping (Tri-PU) is used to ensure the measuring robustness; fringe period extension is achieved by improving overlapping rate to further double the encoding fringe periods for higher measuring accuracy. Based on the proposed measuring technique, one new pixel-to-pixel and unambiguous 3D reconstruction result can be updated with three newly required patterns at a reconstruction rate of 3174 fps. Three transient scenes including collapsing wood blocks struck by a flying arrow, free-falling foam snowflakes and flying water balloon towards metal grids were measured to verify the high performance of the proposed method in various complex dynamic scenes.

High-speed three-dimensional shape measurement based on tripartite complementary Gray-coded light

In phase-shifting profilometry based on the Gray code, the jump error is inevitably generated and is further amplified in dynamic scenes. To tackle this problem, we propose the robust tripartite complementary Gray code method (TCG). Without projecting additional patterns, TCG uses different combinations of Gray code to calculate three complementary orders able to avoid jump error in the unwrapping process. TCG is efficient and robust, as it fully utilizes the redundant information of the Gray code. Experimental results demonstrate that TCG can realize high-efficiency and high-speed three-dimensional shape measurement at a rate of 500 fps.

Phase unwrapping algorithm based on phase edge tracking for dynamic measurement

Phase unwrapping is an essential procedure for fringe projection profilometry (FPP). To improve measurement efficiency and reduce phase unwrapping errors (PUEs) in dynamic measurement, a phase unwrapping algorithm based on phase edge tracking is proposed, which unwraps the current wrapped phase map with the aid of the previously unwrapped one. The phase edges are accurately tracked and their trajectories are used to divide the phase map into several regions, each of which is unwrapped either temporally or spatially according to its properties. It doesn't require extra patterns for phase unwrapping once the initial unwrapped phase map is obtained, thus significantly increasing the frame rate of the 3D result. Meanwhile, it greatly reduces the PUEs caused by noise amplification and motion-induced misalignment of phase edges. Experiments prove that it is capable of retrieving the absolute phase maps of complex dynamic scenes with high unwrapping accuracy and efficiency.

Ultrafast spatial phase unwrapping algorithm with accurately correcting transient phase error

In fringe projection profilometry, the wrapped phase is easily polluted by many factors such as noise, shadow, and so on. In this Letter, we propose an ultrafast bi-staggered spatial phase unwrapping (BSPU) method. By constructing another staggered phase, the fringe order jump (FOJ) and local transient phase error (LTPE) can be accurately and quickly located at the same time owing to a simple difference operation. For the first time, to the best of our knowledge, a pioneering threshold separation model is established to precisely distinguish FOJ and LTPE. Based on the continuity assumption, LTPE is effectively corrected by introducing the concept of "non-integer fringe order." The range of measurable discontinuity height is improved owing to the distinction between real phase jump and random error in the spatial phase unwrapping. In addition, it is thousands of times faster than the traditional path-dependent algorithm and even has higher measurement accuracy. Experimental results show the effectiveness and robustness of the proposed method in various complex measurement environments.