Novel triangular pattern generation method for fast and accurate three-dimensional shape measurement

Fringe projection profilometry (FPP) is a three-dimensional (3D) shape measurement method that involves projecting fringe patterns onto the object. A phase map retrieved from these fringe images is used for reconstructing the 3D surface of the object. Fourier transform and phase-shifting are two of the widely used fringe analysis techniques for performing 3D shape measurement using FPP. Fourier transform profilometry (FTP) has the advantage of performing high-speed measurement due to its single-shot nature. However, the reconstructed 3D surface has artifacts and high noise, specifically on the edges. On the other hand, phase-shifting profilometry (PSP) has the advantage of higher accuracy (relatively less noise level) but compromises on measurement speed. In this research, we propose a deep learning method to enhance the quality of the FTP phase maps using an efficient deep learning model called phase map enhancement net (PMENet). PMENet takes an FTP phase map as input and predicts a high-quality phase map in a supervised manner by using the phase maps obtained from 18-step PSP as ground truth. The training dataset was generated using a virtual FPP system. Validations were conducted on both the simulated data (generated by virtual FPP system) and the real-world data. The experimental results demonstrate that the trained neural network model can successfully improve the quality of the 3D geometric reconstruction with FTP and reduced the mean and root-mean-square error by 66% and 43%, respectively.

Blade is the key component of the aero-engine. In generally, it requires precise size and accurate shape, so the three-dimensional shape measurement of the blade is very important. Fringe projection profilometry is generally used to measure the 3D shape of an object, because of the advantages of non-contact operation, full-field acquisition, high resolution, and fast data processing. In this paper, 3D shape measurement method based on surface structured light that combination of gray-code and phase-shift projection is proposed. The wrapped phase of the blade is got by the four-step phase-shift method. In the projection process of the gray-code, due to the ambient light, different surface reflectance and surface physical discontinuous, the edge of gray-code becomes smooth, leading to decode error, so that the gray-code pattern must be binaried before decode. Through the accurate binarization of the blade gray-code pattern, the decoding cycle of the blade is achieved, and the unwrapped phase is achieved by phase unwrapping. Then the unwrapped phase difference between the blade and reference plane is got, the height of the blade can be obtained by the relationship between the phase difference and the height. The experimental and simulation results show that the proposed method can achieve a high precision, high speed and low cost 3D shape measurement of the blade. The measurement accuracy reaches 0.03 mm. The proposed method extends the reliability and practicality of the fringe projection profilometry.

In this paper, a three-dimensional (3D) shape measurement method based on structured light field imaging is proposed, which contributes to the biomedical imaging. Generally, light field imaging is challenging to accomplish the 3D shape measurement accurately, as the slope estimation method based on radiance consistency is inaccurate. Taking into consideration the special modulation of structured light field, we utilize the phase information to substitute the phase consistency for the radiance consistency in epi-polar image (EPI) at first. Therefore, the 3D coordinates are derived after light field calibration, but the results are coarse due to slope estimation error and need to be corrected. Furthermore, the 3D coordinates refinement is performed based on relationship between the structured light field image and DMD image of the projector, which allows to improve the performance of the 3D shape measurement. The necessary light field camera calibration is described to generalize its application. Subsequently, the effectiveness of the proposed method is demonstrated with a sculpture and compared to the results of a conventional PMP system.

Three-dimensional (3D) shape measurement systems based on diffuse reflection of projected structured light do not deliver reliable data when measuring glossy, transparent, absorbent, or translucent objects. In recent years, we have developed a method based on stereo recording with infrared cameras and projection of areal aperiodic sinusoidal thermal patterns to detect such objects. However, the measurements took longer than 10 s, up to minutes; moreover, the measurement accuracy was improvable. Now, we have succeeded in both drastically reducing measurement time and significantly increasing measurement quality. This finally provides a technique for reliably measuring transparent objects, e.g., in series production. We demonstrate measurement examples achieved within 1 s and with 3D standard deviations less than 10 µm.

This paper presents a novel area-modulated phase-shifting binary method for three-dimensional (3D) shape measurement. First, the defocused triangular binary pattern is introduced to obtain the high-quality sinusoidal fringe without gamma correction. Then, the modified three steps phase-shifting algorithm which includes an average intensity image is adopted to get the wrapped phase and the object mask. After that, a multi-frequency method is used to obtain the unwrapped phase. Finally, a two-step matching method is applied to get the corresponding matching points. The experiments show that the proposed method is more precise and efficient compared with the previous methods.

Color-coded fringe projection profilometry (FPP) is one of the most important single-frame three-dimensional (3D) shape measurement techniques. Transverse chromatic aberration (TCA) in a color-coded FPP system yields imaging deviations, which will result in 3D shape measurement error. In this work, a TCA compensation method for color-coded FPP is proposed. The proposed method establishes the relationship among phase, pixel deviation, and imaging position for decreasing the 3D shape measurement error introduced by TCA. Compared to existing methods that use the relationship among depth, pixel deviation, and imaging position or polynomial fitting for each pixel, the proposed method offers the merits of precise and simple implementation, since it voids the cumulative error in-depth calculation and removes the time-consuming process of polynomial fitting for each pixel. For validation, a color-coded FPP system is established and calibrated. Two verification experiments, including a translation test and 3D shape measurement of a regular spherical object, are conducted with the calibrated system. Experimental results demonstrate that the proposed TCA compensation method is capable of effectively reducing the 3D shape measurement error caused by TCA.

Conventional three-dimensional (3D) shape measurement methods are typically generic to all types of objects. Yet, for many measurement conditions, such a level of generality is inessential when having the preknowledge of the object geometry. This paper introduces a novel adaptive algorithm for absolute 3D shape measurement with the assistance of the object computer-aided-design (CAD) model. The proposed algorithm includes the following major steps: (1)export the 3D point cloud data from the CAD model; (2)transform the CAD model into the camera perspective; (3)obtain a wrapped phase map from three phase-shifted fringe images; and (4)retrieve absolute phase and 3D geometry assisted by the CAD model. We demonstrate that if object CAD models are available, such an algorithm is efficient in recovering absolute 3D geometries of both simple and complex objects with only three phase-shifted fringe images.

Digital speckle correlation (DSC) solves the problem of searching corresponding points between two images, and it shows great application potential in pattern-projection based fast 3D shape measurement, because only one shot is enough to retrieve the 3D structure. As DSC relies on analyzing the spatial intensity distribution of a subset in image with a given point, it is likely to get false correspondences in low quality DSC area such as the background, because the searching range is hard to locate. So it is still hard to use DSC to realize fast 3D shape measurement. To solve this problem, the gray standard deviation of the subset is designed to recognize and remove the low-quality DSC area, and the principle of epipolar geometry and disparity constraint are utilized to determine the searching range, so the correspondences can be obtained. Moreover, in order to enhance the robustness of this method, a connected region method based on neighboring pixels possessing similar disparity is proposed to remove mismatched points after establishing initial disparity map by correspondences. Once the disparity map is obtained 3D structure can be retrieved based on the triangulation principle. The experiment on reconstructing Gorky plaster statue is performed, verifying that the proposed method can substantially reduce mismatched points and achieve robust single frame 3D shape measurement.

The phase-coding method has been widely used for 3D shape measurement, which uses sinusoidal phase-shifting patterns to recover the wrapped phase and the stair phase-coding patterns to determine the fringe order. However, due to random noises and image blurring, the fringe order is always misaligned with the wrapped phase, which will lead to fringe order errors. This paper presents an enhanced phase-coding method to address this misalignment problem by using half-period codewords, in which each codeword is aligned to the half-period of the sinusoidal patterns. Then, two complementary fringe orders with half-period dislocation can be calculated, which can effectively eliminate the fringe order errors. To extend the coding range of stair phase, this paper further develops a computational scheme based on the geometric constraint method. Simulations and experiments have been carried out, and their results confirm that the enhanced method can reliably recover the 3D shape of the measured objects.

To solve the challenging issue of uneven reflectance of high-fidelity surface, this paper proposes a three-dimensional (3D) shape measurement method based on surface adaptation complementary colorimetry-encoded fringe projection profilometry. A complete complementary hue extraction method simulates the retina stimulation to establish the complementary conversion relationship between the projected and collected colors of the measurement system. On this basis, a surface reflectance adaptation fringe pattern encoding strategy is proposed to measure the high-fidelity surfaces. The experiments demonstrate that the proposed method is capable of efficiently balancing and adjusting the reflected light intensity of each fidelity surface, thereby suppressing the ambiguity reconstruction texture. The established complementary colorimetry relationship also improves the light wavelength discrimination, saturation avoidance, measurement accuracy and efficiency.

Binary coding methods have been widely used for three-dimensional (3D) shape measurement. However, traditional binary coding methods always require a sequence of binary patterns to encode the fringe order. This paper presents a spatial-temporal binary coding (STBC) method for 3D shape measurement with three binary patterns, including a spatial pattern and two temporal patterns. Specifically, the spatial pattern is used to encode a 4-bit spatial code, and the temporal patterns are used to encode the 2-bit temporal code. By combining the spatial code and the temporal code, 6-bit code words can be obtained that distinguish 26=64 fringe periods of sinusoidal phase-shifting patterns. A robust dual-region labeling decoding scheme is also developed to extract the 6-bit code word for fringe order determination, and then absolute-phase unwrapping can be carried out. Experiments have been conducted, and their results confirm that the STBC method can reliably reconstruct the 3D shapes of measured objects with only three binary patterns.

A number of works for 3-D shape measurement based on structured light have been well-studied in the last decades. A common way to model the system is to use the binocular stereovision-like model. In this model, the projector is treated as a camera, thus making a projector-camera-based system unified with a well-established traditional binocular stereovision system. After calibrating the projector and camera, a 3-D shape information is obtained by conventional triangulation. However, in such a stereovision-like system, the short baseline problem exists and limits the measurement accuracy. Hence, in this work, we present a new projecting-imaging model based on fringe projection profilometry (FPP). In this model, we first derive a rigorous mathematical relationship that exists between the height of an object’s surface, the phase difference distribution map, and the parameters of the setup. Based on this model, we then study the problem of how the uncertainty of relevant parameters, particularly the baseline’s length, affects the 3-D shape measurement accuracy using our proposed model. We provide an extensive uncertainty analysis on the proposed model through partial derivative analysis, relative error analysis, and sensitivity analysis. Moreover, the Monte Carlo simulation experiment is also conducted which shows that the measurement performance of the projector-camera system has a short baseline.

In fringe projection profilometry, temporal phase unwrapping is an essential procedure to recover an unambiguous absolute phase even in the presence of large discontinuities or spatially isolated surfaces. In this work, a dual-sensitivity profilometry technique is presented, which is based on defocused projection of binary and sinusoidal fringe patterns with a high and low-frequency spatial carrier, respectively. The binary defocusing techniques (based on PWM or square-wave profile patterns, whose pitch is relatively narrow) have demonstrated successful for high-quality three-dimensional shape measurement when the projector presents a nonlinear response. But they suffer if pitch fringe is wide. On the other hand, using dual sensitivity profilometry, the quality of the unwrapped phase is determined by the high-frequency carrier. Thus, working with only one binary pattern, one can use a single defocusing level (low) in order to reduce the data acquisition time and maintain the quality of the unwrapped phase. Experimental results are presented to verify the success of the proposed method.

Fourier transform profilometry (FTP) is one of the frequently adopted three-dimensional (3D) shape measurement methods due to its ability to recover single-shot 3D shapes, yet it is challenging to retrieve the absolute phase map solely from one single grayscale fringe image. This paper presents a computational framework that overcomes this limitation of FTP with digital fringe projection (DFP). By using geometric constraints, an absolute phase map can be retrieved point-by-point from one single grayscale fringe image. Experiments demonstrate the success of our proposed framework with single-shot absolute 3D shape measurement capability.

Rapid and automatic optimal exposure control for digital fringe projection technique