A newly developed flexible calibration algorithm for telecentric 3D measurement systems is presented in this paper. We theoretically analyzed the similarities and differences between the telecentric and entocentric system. The telecentric system can be calibrated with the aid of the traditional 2D planar calibration method. An additional two-step refining process is proposed to improve the calibration accuracy effectively. With the calibration and refining algorithm, an affine camera can be calibrated with a reprojection error of 0.07 pixel. A projector with small field of view (FOV) is applied to achieve a full 3D reconstruction in our profilometry system. Experiments with a prototype demonstrate the validation and accuracy of the proposed calibration algorithm and system configuration. The reconstruction accuracy can achieve 5 µm with a measurement FOV of 28.43 mm×21.33 mm and a working distance of 110 mm.

Flexible calibration method for telecentric fringe projection profilometry systems.

As the size of the radar hardware platform becomes smaller and smaller, the cost becomes lower and lower. The application of indoor radar-based human motion recognition has become a reality, which can be realized in a low-cost device with simple architecture. Compared with narrow-band radar (such as continuous wave radar, etc.), the human motion echo signal of the carrier-free ultra-wideband (UWB) radar contains more abundant characteristic information of human motion, which is helpful for identifying different types of human motion. In this paper, a novel feature extraction method by two-dimensional variational mode decomposition (2D-VMD) algorithm is proposed. And it is used for extracting the primary features of human motion. The 2D-VMD algorithm is an adaptive non-recursive multiscale decomposition method for nonlinear and nonstationary signals. Firstly, the original 2D radar echo signals are decomposed by the 2D-VMD algorithm to capture several 2D intrinsic mode function (BIMFs) which represent different groups of central frequency components of a certain type of human motion. Secondly, original echo signals are reconstructed according to the several BIMFs, which not only have a certain inhibitory effect on the clutter in the echo signal, but can also further demonstrate that the BIMFs obtained by the 2D-VMD algorithm can represent the original 2D echo signal well. Finally, based on the measured ten different types of UWB radar human motion 2D echo analysis signals, the characteristics of these different types of human motion are extracted and the original echo signal are reconstructed. Then, the three indicators of the PCC, UQI, and PSNR between the original echo signals and extraction/reconstruction 2D signals are analyzed, which illustrate the effectiveness of 2D-VMD algorithm to extract feature of human motion 2D echo signals of the carrier-free UWB radar. Experimental results show that BIMFs by 2D-VMD algorithm can well represent the echo signal characteristics of this type of human motion, which is a very effective tool for human motion radar echo signal feature extraction.

https://www.mdpi.com/1424-8220/19/9/1962/pdf

Feature Extraction and Reconstruction by Using 2D-VMD Based on Carrier-Free UWB Radar Application in Human Motion Recognition.

Microscope self-calibration based on micro laser line imaging and soft computing algorithms

Wrist pulse signal acquisition and analysis for disease diagnosis: A review

Precise structural parameter identification of a robotic articulated arm coordinate measuring machine (AACMM) is essential for improving its measuring accuracy, particularly in robotic applications. This paper presents a constructive parameter identification approach for robotic AACMMs. We first develop a mathematical kinematic model of the AACMM based on the Denavit-Hartenberg (DH) approach established for robotic systems. This model is further calibrated and verified via the practical test data. Based on the difference between the calculated coordinates of the AACMM probe via the kinematic model and the given reference coordinates, a parameter identification approach is proposed to estimate the structural parameters in terms of the test data set. The Jacobian matrix is further analyzed to determine the solvability of the identification model. It shows that there are two coupling parameters, which can be removed in the regressor. Finally, a parameter identification algorithm taking the least-square solution of the identification model as the structural parameters by using the obtained poses data is suggested. Practical experiments based on a robotic AACMM test rig are carried out, and the results reveal the effectiveness and robustness of the proposed identification approach.

/pdf/structural-parameter-identification-of-articulated-arm-1gqcaz3zp7.pdf

Structural Parameter Identification of Articulated Arm Coordinate Measuring Machines

The stereo light microscope (SLM) plays an important role in the measurement of three-dimensional geometry on the microscopic scale. We propose a fast and precise affine calibration algorithm based on the invariable extrinsic parameters for the SLM. This calibration algorithm with a free planar reference consists of three steps: first, derive the extrinsic parameters based on their invariable definition in the pinhole and affine models; second, calculate the intrinsic parameters through homography matrix; finally, refine all the model parameters by global optimization with the previous closed-form solutions as the initial values. The effectiveness of assuming a noncoaxial optical system as an affine camera is also verified to affinely model all types of SLMs. The calibration experiments show that the affine calibration is preferable for multicriteria including running time, relative positioning precision, and absolute positioning precision. With PlanApo S 1.5× and a total magnification of 3.024×, the proposed affine calibration algorithm achieves a distance error of 0.423 μm and a positioning error of 0.195 mm within 10.6 s.

Affine calibration based on invariable extrinsic parameters for stereo light microscope

Fast phase denoising using stationary wavelet transform in speckle pattern interferometry

In digital speckle pattern interferometry (DSPI), noise interference leads to a low peak signal-to-noise ratio (PSNR) and measurement errors in the phase map. This paper proposes an adaptive DSPI phase denoising method based on two-dimensional variational mode decomposition (2D-VMD) and mutual information. Firstly, the DSPI phase map is subjected to 2D-VMD in order to obtain a series of band-limited intrinsic mode functions (BLIMFs). Then, on the basis of characteristics of the BLIMFs and in combination with mutual information, a self-adaptive denoising method is proposed to obtain noise-free components containing the primary phase information. The noise-free components are reconstructed to obtain the denoising DSPI phase map. Simulation and experimental results show that the proposed method can effectively reduce noise interference, giving a PSNR that is higher than that of two-dimensional empirical mode decomposition methods.

https://iopscience.iop.org/article/10.1088/1361-6501/aaa380/pdf

Adaptive DSPI phase denoising using mutual information and 2D variational mode decomposition

An approach to precise measurement of small roll angle based on digital speckle pattern interferometry (DSPI) is introduced. A simple relationship between the roll angle and interferometric phase distribution is established by analyzing the mechanism of fringe formation in the process of roll detection using a dual-beam DSPI, and reasonable approximate processing. The presented method enjoys some important advantages, such as being free of a cooperative target and a very high measurement resolution. In our experiments, a measurement resolution of 1 µrad, which can compete with the best resolution of the existing methods, is achieved. Theoretically, the measurement resolution can even be improved to tens of nano-radians at the cost of increasing the size of the measuring device. The performance of the method is also demonstrated by a comparison experiment.

Precision roll angle measurement based on digital speckle pattern interferometry

Pulse diagnosis is one of the four diagnostic methods of traditional Chinese medicine. However it suffers from the lack of objective and efficient detection method. We propose a noncontact optical method to detect human wrist pulse, aiming at the precise determination of the temporal and spatial distributions of pulse. The method uses the spatial-carrier digital speckle pattern interferometry (DSPI) to measure the micro/nanoscale skin displacement dynamically. Significant improvements in DSPI measurement have been made to allow the DSPI to detect the comprehensive information of the arterial pulsation at locations of Cun, Guan, and Chi. The experimental results prove that the spatiotemporal distributions of pulse can be obtained by the proposed method. The obtained data can be further used to describe most of the pulse parameters such as rate, rhythm, depth, length, width, and contour.

Weixian Li

Papers

Affine calibration based on invariable extrinsic parameters for stereo light microscope

Fast phase denoising using stationary wavelet transform in speckle pattern interferometry

Adaptive DSPI phase denoising using mutual information and 2D variational mode decomposition

Precision roll angle measurement based on digital speckle pattern interferometry

Precise Detection of Wrist Pulse Using Digital Speckle Pattern Interferometry.