Improved dual-frequency phase-coding fringe projection method for 3D shape measurement

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.

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.

A height estimating function is proposed based on geometric analysis for a three-dimensional (3-D) measurement system using a digital light processing (DLP) projector and a camera. The proposed 3-D shape measurement method is a hybrid method that combines the geometric parameter measuring method and the least squares method. This method uses the phase-to-height relationship for one line by plane analysis, and the related parameters are estimated using the least squares method. The proposed method has one function per image line instead of one function per image pixel. Sinusoidal fringe patterns of the projector are projected on the object, and the phase of the measuring point is calculated from the camera image. Then, the relationship between the phase by fringe patterns and the height of the measuring point is described as a parameter of the horizontal coordinate on the image plane. Thus, the 3-D shape of the object can be obtained. Our experiments show that the error of the modeling function is within ±0.1 mm when the x-z working range is 100×50 mm. Therefore, the proposed method can dramatically reduce the number of mapping functions needed for 3-D measurement using the geometric relationship between the projector and camera.

Optical full-field measurement techniques have been widely studied in academia and applied to many actual fields of automated inspection, reverse engineering, cosmetic surgery, and so on. With the advent of color CCD cameras and DMD (Digital Micromirror Device) based color DLP (Digital Light Processing) projectors, their major red, green, and blue channels have been used as a carrier to code fringe patterns. Since three fringe patterns can be simultaneously projected and captured at one shot, the acquisition time reduces to 1/3 of the value by the gray fringe pattern projection. This chapter will introduce two kinds of applications of red, green, and blue as a carrier: 1) modulation and demodulation method of coding sinusoidal fringe patterns into RGB channels of a composite color image; and 2) modulation and demodulation method of coding sinusoidal and binary fringe patterns into RGB channels of multiple composite color images. Experiments on testing the two kinds of applications were carried out by measuring the shape of objects’ surface. The results confirm that red, green, and blue channels can be used as a carrier to reduce the acquisition time.

By utilizing 1-bit binary fringe patterns instead of conventional 8-bit sinusoidal patterns, binary defocusing techniques have been successfully applied for high-speed 3D shape measurement. However, simultaneously achieving high accuracy and high speed remains challenging. To overcome this limitation, we propose a high-efficiency and robust binary fringe optimization method for superfast 3D shape measurement, which consists of 1D optimization and 2D modulation. Specifically, for 1D optimization, the three-level OPWM technique is introduced for high-order harmonics elimination, and an optimization framework is presented for generating the 'best' three-level OPWM pattern especially for large fringe periods. For 2D modulation, a single-pattern three-level OPWM strategy is proposed by utilizing all the dimensions for intensity modulation to decrease the required projection patterns. Thus, the proposed method essentially belongs to the 2D modulation technique, yet iterative optimization is carried out along one dimension, which drastically improves the computational efficiency while ensuring high accuracy. With only one set of optimized patterns, both simulations and experiments demonstrate that high-quality phase maps can be consistently generated for a wide range of fringe periods (e.g., from 18 to 1140 pixels) and different amounts of defocusing, and it can achieve superfast and high-accuracy 3D shape measurement.

Palmprint and hand shape, as two kinds of important biometric characteristics, have been widely studied and applied to human identity recognition. The existing research is based mainly on 2D images, which lose the third-dimensional information. The biological features extracted from 2D images are distorted by pressure and rolling, so the subsequent feature matching and recognition are inaccurate. This paper presents a method to acquire accurate 3D shapes of palmprint and hand by projecting full-field composite color sinusoidal fringe patterns and the corresponding color texture information. A 3D imaging system is designed to capture and process the full-field composite color fringe patterns on hand surface. Composite color fringe patterns having the optimum three fringe numbers are generated by software and projected onto the surface of human hand by a digital light processing projector. From another viewpoint, a color CCD camera captures the deformed fringe patterns and saves them for postprocessing. After compensating for the cross talk and chromatic aberration between color channels, three fringe patterns are extracted from three color channels of a captured composite color image. Wrapped phase information can be calculated from the sinusoidal fringe patterns with high precision. At the same time, the absolute phase of each pixel is determined by the optimum three-fringe selection method. After building up the relationship between absolute phase map and 3D shape data, the 3D palmprint and hand are obtained. Color texture information can be directly captured or demodulated from the captured composite fringe pattern images. Experimental results show that the proposed method and system can yield accurate 3D shape and color texture information of the palmprint and hand shape.

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.

Present a novel method of 3D shape measurement of optical free-from surface based on fringe projection. A virtual reference surface is proposed which can be used to improve the detection efficiency and realize the automation of measuring process. Sinusoidal fringe patterns are projected to the high reflected surface of the measured object. The deflection fringe patterns that modulated by the object surface are captured by the CCD camera. The slope information can be obtained by analyzing the relationship between the phase deflectometry and the slope of the object surface. The wave-front reconstruction method is used to reconstruct the surface. With the application of fringe projection technology the accuracy of optical free-form surfaces measurement could reach the level of tens of micrometer or even micrometer.

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.

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.

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.

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.

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.

본 연구에서는 자동 비파괴검사 구현을 위한 3차원 형상 측정 및 경로 설계 방법에 대하여 연구하였다. 2차원 형상 측정 센서에 회전을 추가하여 측정 대상으로부터 취득한 point cloud 데이터는 MATLAB을 이용하여 메시를 생성하여 가시화를 하였다. 가시화된 데이터는 다시 균일한 크기의 메시로 만들고자 메시 재형성을 거쳐 검사 지점과 검사 방향을 산출하였다. 이렇게 산출한 데이터를 이용한 검사 경로는 지그재그로 흔들리는 형상을 가져 비효율적인 경로이므로, 경로 최적화를 진행하였다. 최적화 방법은 검사 방향을 유지하고 검사 위치를 동일한 높이에 배치함으로써 상하로 흔들리는 문제를 제거하였으며 한 층의 검사가 끝나면 초기 위치로 되돌아가는 것이 아니라 바로 위층으로 이동하여 반대 방향으로 검사를 진행하도록 하여 손실되는 경로를 최소화하였다. 이러한 연구를 통하여 형상 정보를 이용한 자동화 비파괴검사 시스템에 대하여 큰 가능성을 확인하였다.

An improved segmented stair phase coding method for 3D shape measurement