Article
Optics
S. Boukhtache, K. Abdelouahab, A. Bahou, F. Berry, B. Blaysat, M. Grediac, F. Sur
Summary: This study aims to customize a convolutional neural network (CNN) for speckle image processing by removing deep layers and reducing the number of filters, resulting in faster image processing. Synthetic images were used to assess the metrological performance of the different versions of the CNN, and real images were tested with the simplified CNN version. The results showed that customization improved the metrological performance of the original CNN version, and the simplified version performed equivalently to the initial version despite drastic simplification.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Engineering, Mechanical
Xiaocen Duan, Jianyong Huang
Summary: With the rapid development of 3D volume imaging technology, digital volume correlation (DVC) has become an indispensable tool in various engineering fields. In this study, a novel deep learning-based DVC methodology called DVC-Net is proposed to achieve accurate and efficient 3D deformation analysis. The method consists of three sub-networks for different tasks, including integer-voxel searching, sub-voxel registration, and displacement field denoising. The DVC-Net reduces computational complexity and is suitable for practical problems such as changes in lighting conditions or noisy images.
EXTREME MECHANICS LETTERS
(2022)
Article
Engineering, Civil
Nur Sila Gulgec, Martin Takac, Shamim N. Pakzad
Summary: This article discusses a method for structural health monitoring using deep neural networks and validates its effectiveness. It first explores the application of Digital Image Correlation in small strain situations, and then evaluates the performance of the damage diagnosis method under two induced damage conditions.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2021)
Article
Engineering, Mechanical
Guoqi Zhao, Xiaoqi Yu, Qinglei Zeng, Shengxin Zhu, Wei Qi, Haosen Chen
Summary: This study investigated the evolution of the local deformation field inside the adiabatic shear band (ASB) using the digital image correlation (DIC) technique. The results revealed the presence of localized deformation and hot-spot formation during the ASB evolution process. These findings contribute to a better understanding of the formation process of ASB.
EXTREME MECHANICS LETTERS
(2022)
Article
Optics
Xiaocen Duan, Hongwei Xu, Runfeng Dong, Feng Lin, Jianyong Huang
Summary: In this study, a new theoretical framework for DIC analysis, called DIC-Net, based on convolutional neural networks is developed. The proposed DIC-Net utilizes a pyramidal structure and second-order shape functions to improve measurement robustness and reliability, as well as computational efficiency. DIC-Net offers an alternative approach to achieve accurate and reliable deformation measurements and has the potential for high-efficiency real-time DIC processing capabilities.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Optics
Zhiwen Chen, Guoliang Xu, Qiang Cao, Meng Ruan, Sheng Liu, Huiming Pan, Li Liu
Summary: This study proposes a method of speckle preparation using pulsed laser for deformation measurement in thin films at elevated temperatures. The method provides good measurement accuracy and minimal damage to the sample.
OPTICS AND LASER TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Zakaria Senousy, Mohamed Medhat Gaber, Mohammed M. Abdelsamea
Summary: Deep learning algorithms can automate the examination of medical images in clinical practice. This paper proposes a new model called AUQantO, which improves the performance of deep learning architectures for medical image classification by optimizing uncertainty quantification techniques and excluding images with high levels of uncertainty.
APPLIED SOFT COMPUTING
(2023)
Article
Optics
Jianhui Zhao, Bing Pan
Summary: Three-dimensional digital image correlation (3D-DIC) is a leading optical measurement technique for measuring full-field shape, displacement, and deformation of solid materials and structures. However, the uncertainty quantification (UQ) of 3D-DIC measurements is less advanced and less widely practiced. This work proposes a Monte Carlo-based method to quantify the uncertainty of 3D-DIC displacement measurements. The proposed method can be integrated with existing 3D-DIC software to quantify the metrological performance of 3D-DIC measurements and therefore better interpret the measurement results.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Chemistry, Analytical
Wei Sun, Zhongda Xu, Xin Li, Zhenning Chen, Xinqiao Tang
Summary: We propose a novel hybrid FPP-DIC technique to measure an object's shape and deformation in 3D simultaneously using a single 3CCD color camera. This technique combines red fluorescent speckles and blue fringe patterns, allowing for the capture of both reference and deformed images. The effectiveness and precision of this method are validated through experimental comparisons.
Article
Engineering, Chemical
Ziran Wu, Yan Han, Bumeng Liang, Guichu Wu, Zhizhou Bao, Weifei Qian
Summary: This paper proposes a metallic fracture estimation method that combines digital image correlation and convolutional neural networks. The method achieves noncontact and nondestructive sensing, as well as high interference immunity. The results of the experiment demonstrate the precision and practicality of the proposed method.
Article
Chemistry, Physical
Hai Yu, Yunpeng Liu, Yunxiang Hu, Mingyang Ta
Summary: This study investigated the effect of gradient interface on the mechanical properties of Cu/WCP functional gradient materials using digital image correlation technique. The experimental results showed that the incorporation of WC particles significantly improved the stiffness and strength of the materials. The plastic strain and strain rate were non-uniform in each layer, and increased along the decreasing direction of WC content. Analysis of the experimental results revealed that the gradient interface had an obvious inhibitory effect on the increase in strain rate, and the location of specimen fracture was related to the strain rate, reflecting the important influence of the gradient interface on the mechanical properties of Cu/WCP functional gradient materials.
Article
Engineering, Industrial
Wu Chengyang, Xiang Sitong, Xiang Wansheng
Summary: This paper utilizes deep learning convolutional neural networks to model the thermal errors of horizontal and vertical spindles, combining thermal images and thermocouple data to create a multi-classification model with high accuracy and robustness. The model's prediction accuracy of 90%-93% outperforms traditional BP models, displaying good robustness even as spindle rotation speed changes. Real cutting tests demonstrate the deep learning model's strong applicability in predicting and compensating for spindle thermal errors.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Software Engineering
Victor Couty, Jean-Francois Witz, Pauline Lecomte-Grosbras, Julien Berthe, Eric Deletombe, Mathias Brieu
Summary: This article introduces an open-source Integrated Digital Image Correlation (I-DIC) software, which is designed to run at high frequencies using CUDA-enabled GPUs. The software uses a global approach for field computation and can be applied in various applications, with one demonstration being a bi-axial tensile test on a cruciform specimen in experimental mechanics.
Article
Construction & Building Technology
Slava Markin, Viktor Mechtcherine
Summary: There is a significant potential for 3D concrete printing to revolutionize the construction industry. To apply this technology practically, it is crucial to address and control the plastic shrinkage and associated cracking. This research introduces an affordable experimental setup and an accurate method for quantifying plastic shrinkage and evaluating shrinkage cracking using 2D digital image correlation.
CEMENT & CONCRETE COMPOSITES
(2023)
Article
Computer Science, Information Systems
Ankit Kumar Jaiswal, Rajeev Srivastava
Summary: This paper presents a method using deep learning to locate tampered regions in forged images. By extending the U-Net segmentation model and adding batch normalization layers and identity-blocks, the challenges of overfitting and information loss are addressed. The proposed model is trained on five different publicly available datasets and tested on four created forged images, showing better performance compared to state-of-the-art techniques.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Optics
Michel Grediac, Benoit Blaysat, Frederic Sur
OPTICS AND LASERS IN ENGINEERING
(2020)
Article
Engineering, Multidisciplinary
Siyi Qin, Michel Grediac, Benoit Blaysat, Shaopeng Ma, Frederic Sur
Summary: This study investigates the effect of sampling density of periodic patterns on noise level in displacement and strain maps using Localized Spectrum Analysis. The parameter is shown to influence noise level, with checkerboards having lower noise level than 2D grids, and the improvement increasing with higher sampling density.
Review
Materials Science, Characterization & Testing
F. Pierron, M. Grediac
Summary: This paper reviews the research on the design and optimization of heterogeneous mechanical tests for identifying material parameters from full-field measurements, termed Material Testing 2.0 (MT2.0).
Article
Computer Science, Hardware & Architecture
Seyfeddine Boukhtache, Benoit Blaysat, Michel Grediac, Francois Berry
Summary: This article introduces a set of algorithms based on linear and cubic interpolations to approximate bicubic interpolation and reduce hardware resource consumption. The algorithms are surveyed and compared in terms of interpolation quality, hardware resource consumption, and other factors.
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Frederic Sur, Benoit Blaysat, Michel Grediac
Summary: The article discusses the importance and limitations of image registration under small displacements in tasks such as optical flow estimation, stereoscopic imaging, and photomechanics. It highlights the significance of quantitatively evaluating the estimation biases and questions the potential for eliminating or reducing these biases. Additionally, numerical assessments of the predictive formula in the context of photomechanics are presented, with freely available software codes to reproduce the results.
JOURNAL OF MATHEMATICAL IMAGING AND VISION
(2021)
Article
Optics
S. Boukhtache, K. Abdelouahab, A. Bahou, F. Berry, B. Blaysat, M. Grediac, F. Sur
Summary: This study aims to customize a convolutional neural network (CNN) for speckle image processing by removing deep layers and reducing the number of filters, resulting in faster image processing. Synthetic images were used to assess the metrological performance of the different versions of the CNN, and real images were tested with the simplified CNN version. The results showed that customization improved the metrological performance of the original CNN version, and the simplified version performed equivalently to the initial version despite drastic simplification.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Materials Science, Multidisciplinary
M. Grediac, X. Balandraud, B. Blaysat, T. Jailin, R. Langlois, F. Sur, A. Vinel
Summary: This study demonstrates that deconvolution with optimized settings is an effective tool for enhancing small and sharp details in strain maps obtained with LSA.
EXPERIMENTAL MECHANICS
(2023)
Proceedings Paper
Engineering, Mechanical
Frederic Sur, Benoit Blaysat, Michel Grediac
Summary: The first objective of this presentation is to explain the cause of the pattern-induced bias observed in displacement fields obtained by local DIC. A model is presented to gather the different errors in retrieving displacement. The study shows that using periodic patterns can significantly reduce the bias.
THERMOMECHANICS & INFRARED IMAGING, INVERSE PROBLEM METHODOLOGIES, MECHANICS OF ADDITIVE & ADVANCED MANUFACTURED MATERIALS, AND ADVANCEMENTS IN OPTICAL METHODS & DIGITAL IMAGE CORRELATION, VOL 4
(2022)
Article
Computer Science, Artificial Intelligence
S. Boukhtache, B. Blaysat, M. Grediac, F. Berry
Summary: This paper studies the optimal hardware implementation of heterogeneous bi-cubic interpolation, improving the algorithm to reduce computational complexity and hardware resource consumption, achieving a compromise in bit-width utilization.
JOURNAL OF REAL-TIME IMAGE PROCESSING
(2021)
Article
Optics
Yin Xiao, Lina Zhou, Wen Chen
Summary: This paper introduces a correspondence imaging approach for reconstructing high-quality objects through complex scattering media. By deriving a rectified theory and introducing temporal correction, the proposed method eliminates the effect of dynamic scaling factors. Experimental results demonstrate the advantages of the proposed method over conventional methods in complex scattering environments, and it can also be combined with other methods to further enhance the quality of reconstructed objects.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Zengxuan Jiang, Minghao Chao, Qingsong Liu, Bo Cheng, Guofeng Song, Jietao Liu
Summary: In this paper, a multi-focal metalens with high focusing efficiency controlled by circular polarization multiplexing is demonstrated. The metalens can generate four transversely distributed focal points under normal incidence of linearly polarized light, supporting both left-circularly polarized and right-circularly polarized conversion. Furthermore, an oblique incidence metalens is designed to achieve high total focusing efficiency for terahertz waves and provides potential new applications for polarization imaging and detection.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Yiran Wang, Yu Ji, Xuyang Zhou, Xiu Wen, Yutong Li, Zhengjun Liu, Shutian Liu
Summary: This work presents a new reconstruction framework for structured illumination microscopy (SIM), which only requires four raw images and avoids extensive iterative computation. By using checkerboard pattern illumination modulation instead of sinusoidal fringe illumination, the proposed method significantly reduces image acquisition time and achieves higher image reconstruction rate. Additionally, the reconstruction process is non-iterative and not limited by the field of view size.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Qian He, Li Pei, Jianshuai Wang, Jingjing Zheng, Tigang Ning, Jing Li
Summary: This paper proposes a 3D refractive index profile visualization method to demonstrate mode activation and evolution in fiber fusion splicing. The method is validated through experimental results and provides support for various fiber splicing operations and mode coupling modulation.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Qiwei Li, Qiyu Wang, Fang Lu, Yang Cao, Xu Zhao
Summary: LSHIP is a lenslet-array-based snapshot hyperspectral imaging polarimeter that combines spectral polarization modulation with integral field imaging spectrometry. It can simultaneously acquire three-dimensional spatial and spectral data-cubes for linear Stokes parameters in a single snapshot.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Huicong Li, Bing Lv, Meng Tian, Wenzhu Huang, Wentao Zhang
Summary: This study proposes a temperature compensation scheme for unbalanced interferometers using sensing fibers with different temperature coefficients, aiming to resolve the temperature disturbance and achieve high strain resolution. The experimental results confirm the effectiveness of the proposed scheme in high-resolution, long-term, low-frequency, and static strain sensing.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Hongxiang Chang, Rongtao Su, Yuqiu Zhang, Bowang Shu, Jinhu Long, Jinyong Leng, Pu Zhou
Summary: High-speed variable-focus optics provides new opportunities for fiber laser applications in various fields. This paper investigates a non-mechanical axial focus tuning method using coherent beam combining (CBC) technique and proposes a tilt modulation assisted method to extend the tuning range.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Yubo Ni, Shuai Fu, Chaoyang Su, Zhaozong Meng, Nan Gao, Zonghua Zhang
Summary: This paper proposes a surface adaptive fringe pattern generation method to accurately measure specular surfaces, eliminating the out-of-focus effect and improving measurement accuracy and reliability.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Zifan Wang, Tianfeng Zhou, Qian Yu, Zihao Zeng, Xibin Wang, Junjian Hu, Jiyong Zeng
Summary: Fast-axis collimation (FAC) lens arrays are crucial in laser systems, and their precision can be improved through the development of an optical collimation system and the use of thermal compensation to correct for non-uniform thermal expansion.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Jincheng Chen, Qiuyu Fang, Li Huang, Xin Ye, Luhong Jin, Heng Zhang, Yinqian Luo, Min Zhu, Luhao Zhang, Baohua Ji, Xiang Tian, Yingke Xu
Summary: This study developed a novel deep learning accelerated SRRF method that enables super-resolution reconstruction with only 5 low SNR images, and allows real-time visualization of microtubule dynamics and interactions with CCPs.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Pan Liu, Yongqiang Zhao, Ning Li, Kai Feng, Seong G. Kong, Chaolong Tang
Summary: This article presents a technique for inverse design of multilayer deep-etched gratings (MDEG) using a deep neural network with adaptive solution space. The proposed method trains a deep neural network to predict the probability distribution across the discretized space, enabling evaluation of an optimal solution. The results show improved efficiencies using only a reduced dataset and avoiding one-to-many mapping challenges.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Evelina Bibikova, Nazar Al-wassiti, Nataliya Kundikova
Summary: Light beams possess three types of angular momentum, namely spin angular momentum, extrinsic orbital angular momentum, and intrinsic orbital angular momentum. The interaction between these momenta leads to the spin-orbit interaction of light and topological effects. This study predicts a new topological effect resulting from the influence of extrinsic orbital angular momentum on spin angular momentum in converging asymmetrical light beams. It manifests as the transformation of linear polarized light into elliptically polarized light when an asymmetrical beam passes through the left or right half of the focal plane. The measured value of the topological circular amplitude anisotropy R was found to be R = +/- (0.60 +/- 0.08) x 10(-3). This new effect contributes to our understanding of light and has potential applications in developing sensors in optics.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Hamdy H. Wahba
Summary: This study combines multiple-beam Fizeau interference and single-shot digital holographic interferometry to study thick phase objects. By collecting optical phase at different focal planes, the angular spectrum method is used for the first time to retrieve optical phase maps through the focal depth. The proposed method proves to be effective in providing accurate numerical focusing and phase maps reconstruction.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Mohammed A. Isa, Richard Leach, David Branson, Samanta Piano
Summary: Due to the complexity of resolving object form and pose in images, new vision algorithms prioritize identification and perception over accurate coordinate measurement. However, the use of planar targets for coordinate measurement in vision systems has several drawbacks, including calibration difficulties and limited viewing angles. On the other hand, the use of sphere targets is infrequent in vision-based coordinate metrology due to the lack of efficient multi-view vision algorithms for accurate sphere measurements.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Optics
Ildar Rakhmatulin, Donald Risbridger, Richard M. Carter, M. J. Daniel Esser, Mustafa Suphi Erden
Summary: This paper reviews the application of machine learning in laser systems. While machine learning has been widely used in general control automation and adjustment tasks, its application in specific tasks requiring skilled workforces for high-precision equipment assembly and adjustment is still limited. The paper presents promising research directions for using machine learning in mirror positional adjustment, triangulation, and optimal laser parameter selection, based on the recommendations of PRISMA.
OPTICS AND LASERS IN ENGINEERING
(2024)