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Effective and robust motion estimation with sub-pixel accuracy is essential in many image processing and computer vision applications. Due to its computational efficiency and robustness in the presence of intensity changes as well as geometric distortions, phase correlation in the Fourier domain provides an attractive solution for global motion estimation and image registration. The paper aims to discuss these issues.

In this paper, relevant sub-pixel strategies are categorized into three classes, namely, single-side peak interpolation, dual-side peak interpolation and curve fitting. The well-known images “Barbara” and “Pentagon” were used to evaluate the performance of eight typical methods, in which Gaussian noise was attached in the synthetic data.

For eight such typical methods, the tests using synthetic data have suggested that considering dual-side peaks in interpolation or fitting helps to produce better results. In addition, dual-side interpolation outperforms curve fitting methods in dealing with noisy samples. Overall, Gaussian-based dual-side interpolation seems the best in the experiments.

Based on the comparisons of eight typical methods, the authors can have a better understanding of the phase correlation for motion estimation. The evaluation can provide useful guidance in this context.

New visual inspection techniques overcome the Nyquist limit to provide high precision measurement of component positions.

This paper aims to propose a non-contact method using machine vision for measuring the surface roughness of a rotating workpiece at speeds of up to 4,000 rpm.

A commercial digital single-lens-reflex camera with high shutter speed and backlight was used to capture a silhouette of the rotating workpiece profile. The roughness profile was extracted at sub-pixel accuracy from the captured images using the moment invariant method of edge detection. The average (Ra), root-mean square (Rq) and peak-to-valley (Rt) roughness parameters were measured for ten different specimens at spindle speeds of up to 4,000 rpm. The roughness values measured using the proposed machine vision system were verified using the stylus profilometer.

The roughness values measured using the proposed method show high correlation (up to 0.997 for Ra) with those determined using the profilometer. The mean differences in Ra, Rq and Rt between the two methods were only 4.66, 3.29 and 3.70 per cent, respectively.

The proposed method has significant potential for application in the in-process roughness measurement and tool condition monitoring from workpiece profile signature during turning, thus, obviating the need to stop the machine.

The machine vision method combined with sub-pixel edge detection has not been applied to measure the roughness of a rotating workpiece.

The purpose of this paper is to propose a sub-pixel calibration method for a microassembly system with coaxial alignment function (MSCA) because traditional sub-pixel calibration approaches cannot be used in this system.

The in-house microassembly system comprises a six degrees of freedom (6-DOF) large motion serial robot with microgrippers, a hexapod 6-DOF precision alignment worktable and a vision system whose optical axis of the microscope is parallel with the horizontal plane. A prism with special coating is fixed in front of the objective lens; thus, two parts’ Figures, namely the images of target and base part, can be acquired simultaneously. The relative discrepancy between the two parts can be calculated from image plane coordinate instead of calculating space transformation matrix. Therefore, the traditional calibration method cannot be applied in this microassembly system. An improved calibration method including the check corner detection solves the distortion coefficient conversely. This new way can detect the corner at sub-pixel accuracy. The experiment proves that the assembly accuracy of the coaxial microassembly system which has been calibrated by the new method can reach micrometer level.

The calibration results indicate that solving the distortion conversely could improve the assembly accuracy of MSCA.

The paper provides certain calibration methodological guidelines for devices with 2 dimensions or 2.5 dimensions, such as microelectromechanical systems devices, using MSCA.

This paper aims to provide an improved multifractal method to extract the pavement cracks in the complicated background. Furthermore, the pavement surface images with or without crack can also be distinguished by this method.

The framework of analyzing the image singularity is based on the sub‐pixel multifractal measure (SPMM). Performing the SPMM can give the sub‐pixel local distribution of the image gradient and a more precise singularity exponent distribution in the image. Meantime, using the singularity exponents and the most singular manifold (MSM), the image can be decomposed into a series of sets with different statistical and physical properties automatically and easily. One can extract the cracks according to the MSM.

The example shows that the physical and geometrical properties of the pavement images can be obtained by analyzing the distribution of singularity exponents and the greatest singularity exponent. The simulation results show that the SPMM has higher quality factor in the image edge detection. And the MSM detected this way reflects the most important information of the image.

Performing the SPMM can give a more precise singularity exponent distribution in the image.

This paper focuses on the design of an inexpensive and accurate range scanner for automatic acquisition of a CAD model of a manufactured part by using two‐dimensional images to determine a digitized three‐dimensional shape. In the developed approach, the object is passed at a speed of 4 cm/s through a single linear laser stripe and forty continuous images are captured into the frame memory of the host computer for subsequent processing. A major problem that is encountered in the design of laser stripe scanner is the specula reflection, which can be mitigated by the developed approach. Six center‐locating algorithms are described, which are central to the developed approach. These algorithms are able to achieve sub‐pixel accuracy. The center of mass algorithm that uses three points, gives the best repeatability over the other algorithms. The center of mass algorithm that uses intensity threshold, provides the best linearity over the other algorithms.

This study aims to present an optical alignment and compensation control of die bonder for chips containing through-silicon vias and develop three-dimensional integrated circuit stacked packaging for compact size and multifunction.

The machine vision, optical alignment method and sub-pixel technology in dynamic imaging condition are used. Through a comparison of reference image, the chip alignment calibration can improve machine accuracy and stability.

According to the experimental data and preliminary results of the analysis, accuracy can be achieved within the desired range, and the accuracy is much better than traditional die bonder equipment. The results help further research in die bonder for chips containing through-silicon vias.

In subsequent testing of the chip, the machine can simultaneously test multiple chips to save test time and increase productivity.

The purpose of this paper is to provide a comprehensive review of a non-contact full-field optical measurement technique known as digital image correlation (DIC).

The approach of this review paper is to introduce the research pertaining to DIC. It comprehensively covers crucial facets including its principles, historical development, core challenges, current research status and practical applications. Additionally, it delves into unresolved issues and outlines future research objectives.

The findings of this review encompass essential aspects of DIC, including core issues like the subpixel registration algorithm, camera calibration, measurement of surface deformation in 3D complex structures and applications in ultra-high-temperature settings. Additionally, the review presents the prevailing strategies for addressing these challenges, the most recent advancements in DIC applications across quasi-static, dynamic, ultra-high-temperature, large-scale and micro-scale engineering domains, along with key directions for future research endeavors.

This review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

The purpose of the work is to provide a comprehensive review of the digital image correlation (DIC) technique for those who are interested in performing the DIC technique in the area of manufacturing.

No methodology was used because the paper is a review article.

no fundings.

Herein, the historical development, main strengths and measurement setup of DIC are introduced. Subsequently, the basic principles of the DIC technique are outlined in detail. The analysis of measurement accuracy associated with experimental factors and correlation algorithms is discussed and some useful recommendations for reducing measurement errors are also offered. Then, the utilization of DIC in different manufacturing fields (e.g. cutting, welding, forming and additive manufacturing) is summarized. Finally, the current challenges and prospects of DIC in intelligent manufacturing are discussed.

The purpose of this paper is to present a new multi-image registration methodology that is able to align a set of hand-held bracketed shots.

The procedure is a two-step algorithm where corresponding multi-image points are automatically extracted from the bracketed image sequence and a least squares adjustment recovers transformation parameters.

The images can be processed with high dynamic range algorithms to combine multiple low dynamic range pictures into a single mosaic with a superior radiometric quality.

Simulated and real examples are illustrated to prove the effectiveness of the developed affine-based procedure.