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Enhancing Crack detection in Critical Structures Using Machine Learning and 3d digital image Correlation

EXPERIMENTAL MECHANICS 2024年第8期64卷 1369-1380页

作者： Holzmond, O. Roache, d. C. Price, M. C. L.Walters, J. Maier, B. R. Li, X. Univ Virginia Dept Mech & Aerosp Engn 122 Engineers Way Charlottesville VA 22903 USA Westinghouse Elect Co Hopkins SC 29061 USA Westinghouse Elect Co Pittsburgh PA 15235 USA

BackgroundThree-dimensional digital image correlation (3d-dIC) is a non-contact monitoring technique that is able to provide accurate three-dimensional strain and displacement measurements. Previous research has shown that 3d-dIC can detect micron-scale cracks in structures as they emerge;however, because 3d-dIC is an optical sensing technique, unfavorable visual conditions due to high heat, large deformations, or a significant distance between the structure and the 3d-dIC cameras can make crack detection difficult or *** research aims to develop machine learning algorithms capable of detecting characteristic crack signals in these *** point velocities obtained via 3d-dIC were transformed into 2d color images for machine learning segmentation. A novel dataset processing technique was utilized to produce the training dataset, which overlayed simplistic crack analogs on top of the first 50 images from the test. different parameters from this technique were investigated to determine their effect on the model's accuracy and *** resulting model detected the onset of significant cracking with an accuracy comparable to acoustic emissions sensors. Varying the processing parameters yielded models that could detect evidence of cracking earlier, at the cost of potentially higher false positive rates. The model also performed well on structures imaged in similar testing setups that were not included in the training *** data processing technique enables crack detection in scenarios where acoustic emissions and other sensors cannot be used. It additionally allows processes already utilizing 3d-dIC to obtain additional information about material performance during testing or operation.

关键词： digital image correlation defect detection Machine learning image segmentation

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Perceptual depth Quality Assessment of Stereoscopic Omnidirectional images

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IEEE TRANSACTIONS ON CIRCUITS ANd SYSTEMS FOR VIdEO TECHNOLOGY 2024年第12期34卷 13452-13462页

作者： Zhou, Wei Wang, Zhou Cardiff Univ Sch Comp Sci & Informat Cardiff CF24 4AG Wales Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

depth perception plays an essential role in the viewer experience for immersive virtual reality (VR) visual environments. However, previous research investigations in the depth quality of 3d/stereoscopic images are rather limited, and in particular, are largely lacking for 3d viewing of 360-degree omnidirectional content. In this work, we make one of the first attempts to develop an objective quality assessment model named depth quality index (dQI) for efficient no-reference (NR) depth quality assessment of stereoscopic omnidirectional images. Motivated by the perceptual characteristics of the human visual system (HVS), the proposed dQI is built upon multi-color-channel, adaptive viewport selection, and interocular discrepancy features. Experimental results demonstrate that the proposed method outperforms state-of-the-art image quality assessment (IQA) and depth quality assessment (dQA) approaches in predicting the perceptual depth quality when tested using both single-viewport and omnidirectional stereoscopic image databases. Furthermore, we demonstrate that combining the proposed depth quality model with existing IQA methods significantly boosts the performance in predicting the overall quality of 3d omnidirectional images.

关键词： Three-dimensional displays Quality assessment Quality of experience image quality Visualization Solid modeling Stereo image processing depth perception overall quality no-reference 3d omnidirectional images multi-color-channel adaptive viewport selection interocular discrepancy human visual system

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Optimization-Based Monocular 3d Object Tracking via Combined Ellipsoid-Cuboid Representation

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IEEE ACCESS 2024年 12卷 109281-109292页

作者： Kim, Gyeong Chan Jang, Youngseok Kim, H. Jin Seoul Natl Univ Dept Aerosp Engn Seoul 08826 South Korea Seoul Natl Univ Automat & Syst Res Inst ASRI Seoul 08826 South Korea Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 08826 South Korea

Monocular 3d object tracking is a challenging task because monocular image lacks depth information necessary for 3d scene understanding. Modern methods typically rely on deep learning to reconstruct 3d information from learned prior, which demands strenuous effort on acquiring ground-truth annotated data and does not generalize for various camera settings. We present a method to continuously track 3d location and orientation of the target object from a monocular image sequence from 2d instance segmentation methods. We reconstruct the structure and trajectory of the objects using factor graph optimization incorporating reprojection error of keypoint tracks, kinematic motion model and bounding box constraints. We propose a combined ellipsoid-cuboid object representation and bounding box constraint to model the object dimension. We evaluate our algorithm in simulation dataset generated using CARLA, and the result indicates that the method is robust to 2d bounding box error and the proposed object representation yields more accurate pose and size estimation compared to solely using either representation.

关键词： Three-dimensional displays Shape Ellipsoids Accuracy Solid modeling Object tracking Estimation Graph optimization monocular vision 3d object tracking

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Super-Resolution Phase Retrieval Network for Single-Pattern Structured Light 3d Imaging

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IEEE TRANSACTIONS ON image processing 2023年 32卷 537-549页

作者： Song, Jianwen Liu, Kai Sowmya, Arcot Sun, Changming Univ New South Wales Sch Comp Sci & Engn Sydney NSW 2052 Australia CSIRO Data61 Epping NSW 1710 Australia Sichuan Univ Coll Elect Engn Chengdu 610065 Peoples R China

Structured light 3d imaging is often used for obtaining accurate 3d information via phase retrieval. Single-pattern structured light 3d imaging is much faster than multi-pattern versions. current phase retrieval methods for single-pattern structured light 3d imaging are however not accurate enough. Besides, the projector resolution in a structured light 3d imaging system is expensive to improve due to hardware costs. To address the issues of low accuracy and low resolution of single-pattern structured light 3d imaging, this work proposes a super-resolution phase retrieval network (SRPRNet). Specifically, a phase-shifting module is proposed to extract multi-scale features with different phase shifts, and a refinement and super-resolution module is proposed to obtain refined and super-resolution phase components. After phase demodulation and unwrapping, high-resolution absolute phase is obtained. A sine shifting loss and a cosine shifting loss are also introduced to form the regularization term of the loss function. As far as can be ascertained, the proposed SRPRNet is the first network for super-resolution phase retrieval by using a single pattern, and it can also be used for standard-resolution phase retrieval. Experimental results on three datasets show that SRPRNet achieves state-of-the-art performance on 1x , 2x , and 4x super-resolution phase retrieval tasks.

关键词： Three-dimensional displays Imaging Superresolution Periodic structures deep learning decoding Feature extraction Structured light super-resolution single-pattern phase retrieval phase-shifting

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A novel approach to visual image encryption:2d hyperchaos,variable Josephus,and 3d diffusion

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Chinese Physics B 2025年第4期34卷 335-352页

作者： Yan Hong Xinyan duan Jingming Su Zhaopan Wang Shihui Fang School of Electrical and Information Engineering Anhui University of Science and TechnologyHuainan 232001China

With the development of the Internet,image encryption technology has become critical for network *** methods often suffer from issues such as insufficient chaos,low randomness in key generation,and poor encryption *** enhance performance,this paper proposes a new encryption algorithm designed to optimize parallel processing and adapt to images of varying sizes and *** method begins by using SHA-384 to extract the hash value of the plaintext image,which is then processed to determine the chaotic system’s initial value and block *** image is padded and divided into blocks for further processing.A novel two-dimensional infinite collapses hyperchaotic map(2dICHM)is employed to generate the intra-block scrambling sequence,while an improved variable Joseph traversal sequence is used for inter-block *** removing the padding,3d forward and backward shift diffusions,controlled by the 2d-ICHM sequences,are applied to the scrambled image,producing the *** results demonstrate that the proposed algorithm outperforms others in terms of entropy,anti-noise resilience,correlation coefficient,robustness,and encryption efficiency.

关键词： SHA-384 two-dimensional infinite collapses hyperchaotic map(2d-ICHM) variable Joseph traversal 3d forward shift diffusion

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ARMedicalSketch: Exploring 3d Sketching for Medical image Using True 2d-3d Interlinked Visualization and Interaction

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2024年第5期54卷 589-598页

作者： Zhang, Nan Huang, Tianqi Liao, Hongen Tsinghua Univ Sch Med Dept Biomed Engn Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China Shanghai Jiao Tong Univ Sch Biomed Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Inst Med Robot Dept Biomed Engn Shanghai 200240 Peoples R China

In traditional clinical practice, doctors often have to deal with 3d information based on 2d-displayed medical images. There is a considerable mismatch between the 2d and 3d dimensions in image interaction during clinical diagnosis, making image manipulation challenging and time-consuming. In this study, we explored 3d sketching for medical images using true 2d-3d interlinked visualization and interaction, presenting a novel AR environment named ARMedicalSketch. It supports image display enhancement preprocessing and 3d interaction tasks for original 3d medical images. Our interaction interface, based on 3d autostereoscopic display technology, provides both floating 3d display and 2d tablet display while enabling glasses-free visualization. We presented a method of 2d-3d interlinked visualization and interaction, employing synchronized projection visualization and a virtual synchronized interactive plane to establish an integrated relationship between 2d and 3d displays. Additionally, we utilized gesture sensors and a 2d touch tablet to capture the user's hand information for convenient interaction. We constructed the prototype and conducted a user study involving 23 students and 2 clinical experts. The controlled study compared our proposed system with a 2d display prototype, showing enhanced efficiency in interacting with medical images while maintaining 2d interaction accuracy, particularly in tasks involving strong 3d spatial correlation. In the future, we aim to further enhance the interaction precision and application scenarios of ARMedicalSketch.

关键词： 3d aerial display augmented reality autostereoscopic visualization human-computer interaction

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Bag of Views: An Appearance-Based Approach to Next-Best-View Planning for 3d Reconstruction

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IEEE ROBOTICS ANd AUTOMATION LETTERS 2024年第1期9卷 295-302页

作者： Gazani, Sara Hatami Tucsok, Matthew Mantegh, Iraj Najjaran, Homayoun Univ Victoria Dept Mech Engn Victoria BC V8P 5C2 Canada Univ British Columbia Okanagan Sch Engn Kelowna BC V1V 1V7 Canada Natl Res Council NRC Canada Montreal PQ H3T 2B2 Canada

UAV-based intelligent data acquisition for 3d reconstruction and monitoring of infrastructure has experienced an increasing surge of interest due to recent advancements in image processing and deep learning-based techniques. View planning is an essential part of this task that dictates the information capture strategy and heavily impacts the quality of the 3d model generated from the captured data. Recent methods have used prior knowledge or partial reconstruction of the target to accomplish view planning for active reconstruction;the former approach poses a challenge for complex or newly identified targets while the latter is computationally expensive. In this work, we present Bag-of-Views (BoV), a fully appearance-based model used to assign utility to the captured views for both offline dataset refinement and online next-best-view (NBV) planning applications targeting the task of 3d reconstruction. With this contribution, we also developed the View Planning Toolbox (VPT), a lightweight package for training and testing machine learning-based view planning frameworks, custom view dataset generation of arbitrary 3d scenes, and 3d reconstruction. Through experiments which pair a BoV-based reinforcement learning model with VPT, we demonstrate the efficacy of our model in reducing the number of required views for high-quality reconstructions in dataset refinement and NBV planning.

关键词： Planning Three-dimensional displays image reconstruction Solid modeling Feature extraction Task analysis Training Aerial systems: perception and autonomy intelligent data acquisition reactive and sensor-based planning

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RWNeRF:Robust Watermarking Scheme for Neural Radiance Fields Based on Invertible Neural Networks

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Computers, Materials & Continua 2024年第9期80卷 4065-4083页

作者： Wenquan Sun Jia Liu Weina dong Lifeng Chen Fuqiang di Department of Cryptographic Engineering Engineering University of PAPXi’an710086China Department of Cryptographic Engineering Key Laboratory of PAP for Cryptology and Information SecurityXi’an710086China

As neural radiance fields continue to advance in 3d content representation,the copyright issues surrounding 3d models oriented towards implicit representation become increasingly *** response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network *** 2d image watermarking technology for 3d scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3d ***,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s *** module restores distorted images through neural network processing before watermark ***,embedding watermarks in each training image enables watermark information extraction from multiple *** proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,*** results demonstrate the efficacy of our scheme in enhancing copyright protection.

关键词： Neural radiance fields 3d scene robust watermarking invertible neural networks

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depth-of-field enhancement in light field display based on fusion of voxel information on the depth plane

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OPTICS ANd LASERS IN ENGINEERING 2024年 183卷

作者： Fu, Bangshao Yu, Xunbo Gao, Xin Xie, Xinhui Shen, Sheng Pei, Xiangyu dong, Haoxiang Yan, Binbin Sang, Xinzhu Beijing Univ Posts & Telecommun BUPT State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

To improve the performance of 3d light field display(LFd) devices and optimize their display effects, a depth-offield (dOF) enhancement in LFd based on fusion of voxel information on the depth plane is proposed. In previous research, a calculation method was developed to calculate the voxel size on the depth plane. According to this calculation method, a distribution model of voxel varying with display depth is established. A dOF determination criterion based on voxel distribution from visual perspective is proposed, and its accuracy is validated through subjective experiments involving multiple participants. By fusing the voxels on the depth plane, the phenomenon of voxel overlap is improved, resulting in enhanced definition of 3d images on the depth plane. Under the condition that the structure and parameters of the 3d LFd device are determined, the maximum achievable display depth will be increased significantly. Finally, experimental validation of the method's feasibility is conducted using multiple 3d light field devices for display.

关键词： Light-field displays depth-of-field 3d image definition Voxel size Voxel distribution

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Elevational Synthetic Aperture Focusing for Rotated Array-Based Three-dimensional Ultrasound Imaging

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IEEE ACCESS 2025年 13卷 45458-45467页

作者： Murakami, Ryo Wang, Yang Tang, Yichuan Tsumura, Ryosuke Fischer, Gregory S. Zhang, Haichong K. Worcester Polytech Inst Dept Robot Engn Worcester MA 01609 USA Worcester Polytech Inst Dept Biomed Engn Worcester MA 01609 USA Worcester Polytech Inst Dept Comp Sci Engn Worcester MA 01609 USA

Three-dimensional (3d) ultrasound (US) imaging is widely used for real-time, non-ionizing, and cost-effective medical diagnostics. However, using a one-dimensional (1d) transducer often results in limited elevational resolution due to the inherent beam thickness. In this paper, we introduce an elevational Synthetic Aperture Focusing (SAF) algorithm specifically designed for rotational 3d US imaging. Unlike previous methods requiring channel data, our approach operates on in-plane beamformed radio-frequency (RF) data, making it more accessible on many commercial scanners. Through simulations and experiments, we demonstrate significant improvements in elevational resolution (up to 96.4%) and contrast (up to 274.7%). These findings highlight the potential of the proposed algorithm to enhance both research and clinical applications of rotational 3d US imaging.

关键词： Imaging Three-dimensional displays Transducers Apertures image resolution Ultrasonic imaging image quality Focusing Probes Radio frequency Biomedical imaging focusing image processing medical diagnostic imaging ultrasonics imaging

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