Limei Song

Application of global phase filtering method in multi frequency measurement

In reverse engineering, reconstruction of 3D point cloud data is the key step to acquire the final profile of the object. However, the quality of 3D reconstruction is influenced by noise in the three-dimensional measurement. This paper aims to tackle the issue of removing the noisy data from the complex point cloud data. The 3D-GPF (Three Dimensional Global Phase Filtering) global phase filtering method is proposed based on the study of phase filtering method, consisting of the steps below. Firstly, the six-step phase shift profilometry is used to obtain the local phase information, and encoding the obtained phase information. Through the global phase unwrapping method, the global phase can be acquired. Secondly, 3D-GPF method is used for the obtained global phase. Finally, the effect of 3D reconstruction is analyzed after the global phase filtering. Experimental results indicate that the noisy points of three-dimensional graphics is reduced 98.02%, the speed of 3D reconstruction is raised 12%.The effect of the proposed global phase filtering method is better than DCT and GSM methods. It is high precision and fast speed, and can be widely used in other 3D reconstruction application.

Shadow removal method for phase-shifting profilometry

In a typical phase-shifting profilometry system for the three-dimensional (3D) shape measurement, shadows often exist in the captured images as the camera and projector probe the object from different directions. The shadow areas do not reflect the fringe patterns which will cause errors in the measurement results. This paper proposed a new method to remove the shadow areas from taking part in the 3D measurement. With the system calibrated and the object reconstructed, the 3D results are mapped on a point-by-point basis into the corresponding positions on the digital micro-mirror device (DMD) of the projector. A set of roles are presented to detect the shadow points based on their mapped positions on the DMD plane. Experimental results are presented to verify the effectiveness of the proposed method.

Improved geometrical model of fringe projection profilometry

The accuracy performance of fringe projection profilometry (FPP) depends on accurate phase-to-height (PTH) mapping and system calibration. The existing PTH mapping is derived based on the condition that the plane formed by axes of camera and projector is perpendicular to the reference plane, and measurement error occurs when the condition is not met. In this paper, a new geometric model for FPP is presented to lift the condition, resulting in a new PTH mapping relationship. The new model involves seven parameters, and a new system calibration method is proposed to determine their values. Experiments are conducted to verify the performance of the proposed technique, showing a noticeable improvement in the accuracy of 3D shape measurement.

A composite quality-guided phase unwrapping algorithm for fast 3D profile measurement

Fringe pattern profilometry (FPP) is one of the most promising 3D profile measurement techniques, which has been widely applied in many areas. A challenge problem associated with FPP is the unwrapping of wrapped phase maps resulted from complex object surface shapes. Although existing quality-guided phase unwrapping algorithms are able to solve such a problem, they are usually extensively computational expensive and not able to be applied to fast 3D measurement scenarios. This paper proposes a new quality-guided phase unwrapping algorithm with higher computational efficiency than the conventional ones. In the proposed method, a threshold of quality value is used to classify pixels on the phase maps into two types: high quality (HQ) pixels corresponding to smooth phase changes and low quality (LQ) ones to rough phase variance. In order to improve the computational efficiency, the HQ pixels are unwrapped by a computationally efficient fast phase unwrapping algorithm, and the LQ pixels are unwrapped by computational expensive flood-fill algorithm. Experiments show that the proposed approach is able to recover complex phase maps with the similar accuracy performance as the conventional quality-guided phase unwrapping algorithm but is much faster than the later.

3D shape measurement based on projection of triangular patterns of two selected frequencies

In this paper, a temporal shift unwrapping technique is presented for solving the problem of shift wrapping associated with spatial shift estimation (SSE)-based fringe pattern profilometry (FPP). Based on this technique, a novel 3D shape measurement method is proposed, where triangular patterns of two different spatial frequencies are projected. The patterns of the higher frequency are used to implement the FPP, and the one with lower frequency is utilized to achieve shift unwrapping. The proposed method is able to solve the shift unwrapping problem associated with the existing multi-step triangular pattern FPP by projection of an additional fringe pattern. The effectiveness of the proposed method is verified by experimental results, where the same accuracy as existing multi-step triangular pattern FPP can be achieved, but enabling the measurement of objects with complex surface shape and high steps.

Fringe Pattern Analysis With Message Passing Based Expectation Maximization for Fringe Projection Profilometry

Fringe projection profilometry (FPP) is a popular optical 3-D imaging approach, in which the images of deformed fringe patterns are analyzed to extract object surfaces (i.e., height maps of object surfaces). As an object surface normally does not change independently, height correlations of an object surface can be used to denoise and improve the measurement performance of the FPP. This paper investigates the issue of exploiting height correlations in FPP fringe pattern analysis. The challenge lies in that height correlations are unknown and they are different from object to object. In addition, the problem of interest is normally in a large scale. In this paper, we use autoregressive (AR) models with unknown parameters to model the unknown height correlations and formulate the FPP analysis problem (with height correlations exploited) under the framework of expectation maximization (EM). With EM, the unknown AR model parameters are determined based on observations, and the estimates of the heights with their correlations exploited can also be extracted. To deal with the large-scale problem, a message passing-based implementation of the formulated EM problem is studied and the relevant message updating rules are developed. The proposed approach has a linear complexity and it allows parallel processing due to the nature of message passing. Simulation and experimental results demonstrate a significant performance improvement by the proposed approach.

Three-Dimensional Virtual Surgery Based on CT Images

Virtual surgery is very important for doctors to ensure the success before real surgery. By combining VTK and ITK with MFC, three-dimensional reconstruction of sequence of medical images and virtual cutting system are achieved, and a three-dimensional virtual surgery system is developed. The system offers the function such as 3-D surface rendering, 3-D volume rendering, medical volume data segmentation, virtual surgical cutting, 3-D measurement, virtual surgical planning and so on. The system can help surgeons to observe 3-D models of human organs, parenchyma and the focus of a disease and carry out computer aided surgical. Key words-VTK; 3-D reconstruction; medical volume data segmentation; virtual cutting; virtual surgery

Two Cameras Vision Model for the 3D Shape Recovery

One camera can get the image of the object, but it is difficult to get the precision three dimension shape of the object. Two cameras can get the precision dimension of the object just like human two eyes. The two camera vision model is built in this paper. The two cameras are placed to look common area. After the two cameras are calibrated, they can get the precision 3D coordinate of the object. The merits of the two camera vision system are that it can get the real exact shape of the object with fast speed. And it can be extended to a lot of 3D measurement system.

Hollow waveguide-enhanced mid-infrared sensor for fast and sensitive ethylene detection

Purpose This paper aims to provide a sensor for fast, sensitive and selective ethylene (C2H4) concentration measurements. Design/methodology/approach The paper developed a sensor platform based on tunable laser absorption spectroscopy with a 3,266-nm interband cascade laser (ICL) as an optical source and a hollow waveguide (HWG) as a gas cell. The ICL wavelength was scanned across a C2H4 strong fundamental absorption band, and an interference-free C2H4 absorption line located at 3,060.76 cm−1 was selected. Wavelength modulation spectroscopy with the second harmonic detection (WMS-2f) technique was used to improve the sensitivity. Furthermore, the HWG gas cell can achieve a long optical path in a very small volume to improve the time response. Findings The results show excellent linearity of the measured 2f signal and the C2H4 concentration with a correlation coefficient of 0.9997. Also, the response time is as short as about 10 s. The Allan variance analysis indicates that the detection limit can achieve 53 ppb with an integration time of 24 s. Practical implications The ethylene sensor has many meaningful applications in environmental monitoring, industrial production, national security and the biomedicine field. Originality/value The paper provides a novel sensor architecture which can be a versatile sensor platform for fast and sensitive trace-gas detection in the mid-infrared region.

An object image edge detection based quality-guided phase unwrapping approach for fast three-dimensional measurement

A new approach for achieving fast and reliable unwrapping of complex phase maps is presented for phase shifted based three-dimensional (3D) Fringe pattern profilometry (FPP). As phase unwrapping errors are often caused by shadows on fringe patterns images and object surface discontinuities, we propose to identify both of them. An image of the object is acquired by averaging the fringe patterns reflected from the object surface, based on which shadow areas and the phase discontinuities are identified. When carrying out phase unwrapping, the shadow areas and the edge pixels will be isolated, and then the remaining areas are unwrapped by means of an efficient technique proposed below. All the remaining pixels are then unwrapped by an efficient technique proposed, by which, the computational efficiency can be significantly improved. As proven by the experiment results, the proposed approach is able to implement fast and reliable phase unwrapping.