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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.

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 propose a methodology to quantify the error on wear volume evaluation using optical interferometry with image analysis (OI+IA), to establish a lower threshold for wear mapping in practical applications.

A three-dimensional surface wear map is quantified by measuring the same area of a surface before and after a wear process using optical interferometry. Then, by subtracting the matching images, the wear map (volume of wear) is obtained. To access the error related to wear mapping, the difference between several consecutive measurements of the same unworn surface was performed and deeply investigated.

The paper shows that the difference between two consecutive measurements of the same unworn surface, which ideally should be zero, is not. Thus, the magnitude of this “wear map” is the error. The main causes of such uncertainties are because of sample motion in a subpixel scale; a combination between surface roughness with the selected resolution; and numerical errors on the relocation process that is used to match the surfaces before subtracting them.

The proposed methodology allows one to define the lower threshold for wear map analysis using OI+IA. To know the limitation of OI+IA for wear mapping prevents misevaluation of the so-called almost-zero-wear.

This paper covers and identifies main uncertainties and numerical errors related to optical interferometry assisted by image analysis for wear mapping. Several other papers deal with uncertainties of OI; however, this paper proposes a simple methodology to evaluate the lower threshold for wear mapping.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0354

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.

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.

This paper aims to present an adaptation of digital image correlation (DIC) to the electronics industry for reliability assessment of electronic packages. Two case studies are presented: one for warpage measurement of a micro-electro-mechanical system (MEMS) package under different temperature conditions and the other for the measurement of transient displacements on the surface of a printed circuit board (PCB) assembly under free-fall drop conditions, which is for explaining the typical camera setup requirement and comparing among different boundary conditions by fastening methods of PCB.

DIC warpage measurements on a small device, such as a MEMS package, require a special speckle pattern. A new method for the creation of speckle patterns was developed using carbon coating and aluminum evaporative deposition. To measure the transient response on the surface of a PCB during a free-fall impact event, three-dimensional (3D) DIC was integrated with synchronized stereo-high speed cameras. This approach enables the measurement of full-field displacement on the PCB surface during a free-fall impact event, contrary to the localized information that is obtained by the conventional strain gage and accelerometer method.

The authors suggest the proposed patterning method to the small-sized microelectronics packages for DIC measurements. More generally, the idea is to have a thin layer of the dark or bright color of the background and then apply the white or black colored pattern, respectively, so that the surface has high contrast. Also, to achieve a proper size of speckles, this paper does not want to expose the measuring objects to high temperatures or pressures during the sample preparation stage. Of course, it seems a complicated process to use aluminum evaporator, carbon coater and electroformed mesh. However, the authors intend to share one of the solutions to achieve a proper pattern on such small-sized electronic packages.

3D DIC technique can be successfully implemented for the measurement of micro-scale deformations in small packages (such as MEMS) and for the analysis of dynamic deformation of complex PCB.

Laser scanning is increasingly used in many three‐dimensional (3‐D) measurement and modeling applications. It is the latest technique used in 3‐D measurement, and is becoming increasingly important within a number of applications. However, many applications require photogrammetric data in addition to laser scanning data. The purpose of this paper is to present a range and image sensor combination for three‐dimensional reconstruction of objects or scenes.

In this study, a Nikon D80 camera was mounted on an Ilris 3D laser scanner and CPP was estimated according to the laser scanner coordinate system. The estimated CPP was controlled using three different methods which were developed in this study and a sample application as coloring of point cloud using image taken by the camera mounted on the laser scanner was performed.

It was found that when a high‐resolution camera is mounted on laser scanners, camera position parameters (CPP) should be estimated very accurately with respect to the laser scanner coordinate system.

The paper shows that the combination of high‐resolution camera and laser scanners should be used for more accurate and efficient results in 3D modeling applications.

This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum industry.

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) is initially used to identify key barriers as reported in extant literature. The decision-making trial and evaluation laboratory (DEMATEL) technique is then used to discover the interrelationships between the barriers, which are then prioritised, based on three criteria (time, cost and relative importance) using complex proportional assessment (COPRAS) and multi-objective optimisation method by ratio analysis (MOORA). The Delphi method is used to obtain and analyse data from 10 petroleum experts who work at various petroleum facilities in India.

The findings provide practical insights for management and accident data analysts to use ML techniques when analysing large amounts of data. The analysis of barriers will help organisations focus resources on the most significant obstacles to overcome barriers to adopt ML as the primary tool for accident data analysis, which can save time, money and enable the exploration of valuable insights from the data.

This is the first study to use a hybrid three-phase methodology and consult with domain experts in the petroleum industry to rank and analyse the relationship between these barriers.

This paper aims to present a mosaicking method for underwater robotic applications, whose result can be provided to other perceptual systems for scene understanding such as real-time object recognition.

This method is called robust and large-scale mosaicking (ROLAMOS) and presents an efficient frame-to-frame motion estimation with outlier removal and consistency checking that maps large visual areas in high resolution. The visual mosaic of the sea-floor is created on-the-fly by a robust registration procedure that composes monocular observations and manages the computational resources. Moreover, the registration process of ROLAMOS aligns the observation to the existing mosaic.

A comprehensive set of experiments compares the performance of ROLAMOS to other similar approaches, using both data sets (publicly available) and live data obtained by a ROV operating in real scenes. The results demonstrate that ROLAMOS is adequate for mapping of sea-floor scenarios as it provides accurate information from the seabed, which is of extreme importance for autonomous robots surveying the environment that does not rely on specialized computers.

The ROLAMOS is suitable for robotic applications that require an online, robust and effective technique to reconstruct the underwater environment from only visual information.

The assembly of large component in out-field is an important part for the usage and maintenance of aircrafts, which is mostly manually accomplished at present, as the commonly used large-volume measurement systems are usually inapplicable. This paper aims to propose a novel coaxial alignment method for large aircraft component assembly using distributed monocular vision.

For each of the mating holes on the components, a monocular vision module is applied to measure the poses of holes, which together shape a distributed monocular vision system. A new unconstrained hole pose optimization model is developed considering the complicated wearing on hole edges, and it is solved by a iterative reweighted particle swarm optimization (IR-PSO) method. Based on the obtained poses of holes, a Plücker line coordinates-based method is proposed for the relative posture evaluation between the components, and the analytical solution of posture parameters is derived. The required movements for coaxial alignment are finally calculated using the kinematics model of parallel mechanism.

The IR-PSO method derived more accurate hole pose arguments than the state-of-the-art method under complicated wearing situation of holes, and is much more efficient due to the elimination of constraints. The accuracy of the Plücker line coordinates-based relative posture evaluation (PRPE) method is competitive with the singular value decomposition (SVD) method, but it does not rely on the corresponding of point set; thus, it is more appropriate for coaxial alignment.

An automatic coaxial alignment system (ACAS) has been developed for the assembly of a large pilotless aircraft, and a coaxial error of 0.04 mm is realized.

The IR-PSO method can be applied for pose optimization of other cylindrical object, and the analytical solution of Plücker line coordinates-based axes registration is derived for the first time.