Xinjun Zhu

Structured-light based 3D reconstruction system for cultural relic packaging

The non-contact three-dimensional measurement and reconstruction techniques have played a significant role in the packaging and transportation of precious cultural relics. This paper develops a structured light based three-dimensional measurement system, with a low-cost for cultural relics packaging. The structured light based system performs rapid measurements and generates 3D point cloud data, which is then denoised, registered and merged to achieve accurate 3D reconstruction for cultural relics. The multi-frequency heterodyne method and the method in this paper are compared. It is shown that the relative accuracy of the proposed low-cost system can reach a level of 1/1000. The high efficiency of the system is demonstrated through experimental results.

Information-weighted constrained regularization for particle size distribution recovery in multiangle dynamic light scattering

In particle size measurement with dynamic light scattering (DLS), it is difficult to get an accurate recovery of a bimodal particle size distribution (PSD) with a peak position ratio less than ~2:1, especially when large particles (>350nm) are present. This is due to the inherent noise in the autocorrelation function (ACF) data and the scarce utilization of PSD information during the inversion process. In this paper, the PSD information distribution in the ACF data is investigated. It was found that the initial decay section of the ACF contains more information, especially for a bimodal PSD. Based on this, an information-weighted constrained regularization (IWCR) method is proposed in this paper and applied in multiangle DLS analysis for bimodal PSD recovery. By using larger (or smaller) coefficients for weighting the ACF data, more (or less) weight can then be given to the initial part of the ACF. In this way, the IWCR method can enhance utilization of the PSD information in the ACF data, and effectively weaken the effect of noise at large delay time on PSD recovery. Using this method, bimodal PSDs (with nominal diameters of 400:608 nm, 448:608 nm, 500:600 nm) were recovered successfully from simulated data and it appears that the IWCR method can improve the recovery resolution for closely spaced bimodal particles. Results of the PSD recovery from experimental DLS data confirm the performance of this method.

Assessment of Fringe Pattern Decomposition with a Cross-Correlation Index for Phase Retrieval in Fringe Projection 3D Measurements

Phase retrieval from single frame projection fringe patterns, a fundamental and challenging problem in fringe projection measurement, attracts wide attention and various new methods have emerged to address this challenge. Many phase retrieval methods are based on the decomposition of fringe patterns into a background part and a fringe part, and then the phase is obtained from the decomposed fringe part. However, the decomposition results are subject to the selection of model parameters, which is usually performed manually by trial and error due to the lack of decomposition assessment rules under a no ground truth data situation. In this paper, we propose a cross-correlation index to assess the decomposition and phase retrieval results without the need of ground truth data. The feasibility of the proposed metric is verified by simulated and real fringe patterns with the well-known Fourier transform method and recently proposed Shearlet transform method. This work contributes to the automatic phase retrieval and three-dimensional (3D) measurement with less human intervention, and can be potentially employed in other fields such as phase retrieval in digital holography.

Lp-norm-residual constrained regularization model for estimation of particle size distribution in dynamic light scattering

In particle size measurement using dynamic light scattering (DLS), noise makes the estimation of the particle size distribution (PSD) from the autocorrelation function data unreliable, and a regularization technique is usually required to estimate a reasonable PSD. In this paper, we propose an Lp-norm-residual constrained regularization model for the estimation of the PSD from DLS data based on the Lp norm of the fitting residual. Our model is a generalization of the existing, commonly used L2-norm-residual-based regularization methods such as CONTIN and constrained Tikhonov regularization. The estimation of PSDs by the proposed model, using different Lp norms of the fitting residual for p=1, 2, 10, and ∞, is studied and their performance is determined using simulated and experimental data. Results show that our proposed model with p=1 is less sensitive to noise and improves stability and accuracy in the estimation of PSDs for unimodal and bimodal systems. The model with p=1 is particularly applicable to the noisy or bimodal PSD cases.

Integrated real-time measurement method of filament lamp dimension based on machine vision

An integrated method is proposed for the real-time measurement of filament lamp dimension based on machine vision (FLDMV). First, an online detection platform is built, and the image is acquired by telecentric lenses and charge-coupled diode (CCD). Second, a series of image processing, including filter, edge extraction, ellipse fitting, recursive minimum bounding rectangle, and curvature restrict estimation. Finally, the actual size of lamp is obtained by system calibration. The experimental analysis and comparison show that the maximum measurement error of this method is 0.21mm, which meets the requirements of filament lamp dimension measurement. The curvature restrict estimation based on ellipse fitting are proposed to guarantee the accuracy and real time. Compared with the traditional measurement method, our method has the advantages of fast measurement speed, high accuracy, and real time. It also can be widely used in other parts of the measurement.