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In fringe projection profilometry (FPP), the phase-shifting profilometry (PSP) is widely used in various fields such as industrial quality check and biomechanics. Among the methods of PSP for absolute phase retrieval, stereo phase unwrapping method, as a new-fashioned method, can eliminate the 2π phase ambiguities and obtain a continuous phase map with a stereo vision system, retrieving the correct fringe period with geometry constraints and depth constraints and not needing to project any additional patterns. However, ensuring the stability of stereo phase unwrapping, the frequency of fringe patterns should be limited at about 20, which affects the accuracy of the 3D shape measurement. Furthermore, in order to enhance the performance of stereo phase unwrapping, stereo block matching based on the speckles as additional auxiliary information is used, which can distinguish several periodic candidate points but still not avoid mismatches, especially for the areas of the dark regions and the object edges where the fringe quality is low. To solve these problems, we proposed a robust absolute 3D measurement using stereo cost-volume filtering for fringe orders in this paper. In the proposed method, besides the stereo block matching, a matching cost filter is designed to aggregate the preliminary matching cost for the final cost which is used to obtain the fringe order map by WTA and then the absolute phase map. Then the more robust and more accurate 3D measurement is realized compared with traditional methods. The experimental results demonstrate that the proposed method can achieve robust absolute 3D measurement using stereo phase unwrapping.

In this paper, we propose a fast stereo 3D imaging technique based on random speckle projection and its FPGA implementation. Stereo vision, as a classic passive method for 3D shape measurement based on the multi-view geometric constraints, can realize the 3D reconstruction of the tested scene using a pair of images captured through the binocular cameras. In addition, some complicated matching techniques, such as graph cut and block matching, are used to obtain a global disparity map but it leads to massive computing overhead. To solve this problem, we developed a fast stereo vision system based on FPGA. Benefiting from the full parallel architecture of FPGA, the complete computational framework is based on a full pipeline design, that is, the storage and calculation of data are performed under the system clock to implement different works of stereo vision (including stereo rectify and stereo matching) at the same time, promoting calculation speed and measurement efficiency. In order to further improve the accuracy of 3D measurement, by introducing structured light illumination into the existing system, a projection system based on random speckle is designed where fast speckle projection and synchronous acquisition are realized on the FPGA hardware. Experimental results verify that our method can achieve high-speed and robust 3D shape measurement.

Since a slight variance in production processes can make the entire production run defective, defect inspections are indispensable procedures in manufacturing processes to ensure high quality of each item before entering the next manufacturing step. Three-dimensional (3D) optical shape measurement technologies are widely applied for surface defect inspection of complex workpieces because of its high-accuracy and digitization. However, the complex surface structure and position of the test object can pose serious challenges, making inspections still relatively slow, expensive, and complicated in implementation and maintenance. In this work, we propose a real-time 360∘ 3D surface defect inspection approach based on fringe projection profilometry without any auxiliary equipment for position control. Firstly, a multi-view 3D measurement based on geometric constraints is employed to acquire high-accuracy depth information from different perspectives. Then, a cycle-positioning-based registration scheme with the establishment of the pose-information-matched 3D standard digital model is proposed to realize rapid alignment of the measured point cloud and the standard model. Finally, a minimum 3D distance search is driven by a dual-thread processing mechanism for simultaneous scanning and detecting to quantify and locate 3D surface defects in real time. Experimental results show that our method can accurately identify the surface defects of complicated objects in real time in an extremely simple (hand-held) manner, saving a lot of operational expenses on precision alignment and position-orientation adjustment. The proposed method holds tremendous potential for quality control in many facets of industry, such as product development, testing, and manufacturing.