Feifei Gu

Phase unwrapping algorithm based on multi-frequency fringe projection and fringe background for fringe projection profilometry

A phase unwrapping algorithm specially designed for the phase-shifting fringe projection profilometry (FPP) is proposed. It combines a revised dual-frequency fringe projectionalgorithm and a proposed fringe background based quality guided phase unwrapping algorithm (FB-QGPUA). Phase demodulated from the high-frequency fringe patterns is partially unwrapped by that demodulated from the low-frequency ones. Then FB-QGPUA is adopted to further unwrap the partially unwrapped phase. Influences of the phase error on the measurement are researched. Strategy to select the fringe pitch is given. Experiments demonstrate that the proposed method is very robust and efficient.

Color fringe-projected technique for measuring dynamic objects based on bidimensional empirical mode decomposition

A triple-frequency color fringe-projected technique is presented to measure dynamic objects. Three fringe patterns with a carrier frequency ratio of 1:3:9 are encoded in red, green, and blue channels of a color fringe pattern and projected onto an objects surface. Bidimensional empirical mode decomposition is used for decoupling the cross talk among color channels and for extracting the fundamental frequency components of the three fringe patterns. The unwrapped phase distribution of the high-frequency fringe is retrieved by a three-step phase unwrapping strategy to recover the objects height distribution. Owing to its use of only a single snapshot, the technique is suitable for measuring dynamically changing objects with large discontinuity or spatially isolated surfaces.

Camera calibration based on the back projection process

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

Non-null testing for aspheric surfaces using elliptical sub-aperture stitching technique

We propose an elliptical sub-aperture stitching (ESAS) method to measure the aspheric surfaces. In our method, the non-null configuration is used to overcome the disadvantages of the null testing. By adding the dynamic tilt, the different local nearly null fringe patterns are obtained and the corresponding phase data in the elliptical masks is extracted with negligible retrace errors. In order to obtain the full aperture result, a stitching algorithm is developed to stitch all the phase data together. We firstly show the principle of our method. Then the performance of the proposed method is analyzed by simulation experiments. In the end, practical examples are given to demonstrate the correctness of the proposed method. The stitching result shows a good agreement with the full-aperture null testing result.

Calibration of stereo rigs based on the backward projection process

High-accuracy 3D measurement based on binocular vision system is heavily dependent on the accurate calibration of two rigidly-fixed cameras. In most traditional calibration methods, stereo parameters are iteratively optimized through the forward imaging process (FIP). However, the results can only guarantee the minimal 2D pixel errors, but not the minimal 3D reconstruction errors. To address this problem, a simple method to calibrate a stereo rig based on the backward projection process (BPP) is proposed. The position of a spatial point can be determined separately from each camera by planar constraints provided by the planar pattern target. Then combined with pre-defined spatial points, intrinsic and extrinsic parameters of the stereo-rig can be optimized by minimizing the total 3D errors of both left and right cameras. An extensive performance study for the method in the presence of image noise and lens distortions is implemented. Experiments conducted on synthetic and real data demonstrate the accuracy and robustness of the proposed method.

Photometric invariant stereo matching method

A robust stereo matching method based on a comprehensive mathematical model for color formation process is proposed to estimate the disparity map of stereo images with noise and photometric variations. The band-pass filter with DoP kernel is firstly used to filter out noise component of the stereo images. Then the log-chromaticity normalization process is applied to eliminate the influence of lightning geometry. All the other factors that may influence the color formation process are removed through the disparity estimation process with a specific matching cost. Performance of the developed method is evaluated by comparing with some up-to-date algorithms. Experimental results are presented to demonstrate the robustness and accuracy of the method.

Lateral location error compensation algorithm for measuring aspheric surfaces by sub-aperture stitching interferometry

Sub-aperture stitching (SAS) testing method is an effective way to extend the lateral and vertical dynamic range of a conventional interferometer. However, the center of each sub-aperture could be in error because of the complex motion of the mechanical platform. To eliminate the affection of lateral location error in the final stitching result, a lateral location error compensation algorithm is introduced and the ability of the algorithm to compensate the lateral location error is analyzed. Finally, a 152.4mm concave parabolic mirror is tested using SAS method with the compensation algorithm. The result showed that the algorithm can effectively compensate the lateral location error caused by the mechanical motion. The proposal of the algorithm can reduce high requirement of mechanical platform, which provides a feasible method for the practical application of the engineering.

Technique for positioning moving binocular vision measurement system and data registration with ball target

A ball-based intermediary target technique is presented to position moving machine vision measurement system and to realize data registration under different positions. Large-sized work-piece measurement based on machine vision faces several problems: limited viewing angle, range and accuracy of measurement inversely proportional. To measure the whole work-piece conveniently and precisely, the idea that using balls as registration target is proposed in this paper. Only a single image of the ball target is required from each camera then the vision system is fully calibrated (intrinsic and extrinsic camera parameters). When the vision system has to be moved to measure the whole work-piece, one snapshot of the ball target in the common view can position the system. Then data registration can be fulfilled. To achieve more accurate position of ball’s center, an error correction model is established.

The error analysis of the handheld target in Target-based Vision Measurement System (T-VMS)

The handheld target greatly expands the fields of the vision measurement systems. However, it introduces extraction errors and position errors, which degrades the positioning precision of the vision measurement systems. In order to evaluate the influence of the handheld targets on the accuracy of T-VMS, we first analyzed the positioning principle of the visual measurement system and established the precision model under two typical structures of the T-VMS. We then studied the extraction errors and position errors introduced by the handheld targets and quantified the errors. Finally, we discussed the influence of the said errors on the positioning in 3D space with system precision model. We applied the precision model in an actual T-VMS to confirm its feasibility and effectiveness, and found that it indeed estimate the errors introduced by the handheld targets effectively.

Global stereo matching algorithm based on disparity range estimation

The global stereo matching algorithms are of high accuracy for the estimation of disparity map, but the time-consuming in the optimization process still faces a curse, especially for the image pairs with high resolution and large baseline setting. To improve the computational efficiency of the global algorithms, a disparity range estimation scheme for the global stereo matching is proposed to estimate the disparity map of rectified stereo images in this paper. The projective geometry in a parallel binocular stereo vision is investigated to reveal a relationship between two disparities at each pixel in the rectified stereo images with different baselines, which can be used to quickly obtain a predicted disparity map in a long baseline setting estimated by that in the small one. Then, the drastically reduced disparity ranges at each pixel under a long baseline setting can be determined by the predicted disparity map. Furthermore, the disparity range estimation scheme is introduced into the graph cuts with expansion moves to estimate the precise disparity map, which can greatly save the cost of computing without loss of accuracy in the stereo matching, especially for the dense global stereo matching, compared to the traditional algorithm. Experimental results with the Middlebury stereo datasets are presented to demonstrate the validity and efficiency of the proposed algorithm.