Subpixel Matching Using Double-Precision Gradient-Based Method for Digital Image Correlation

Liu, Gang; Li, Mengzhu; Zhang, Weiqing; Gu, Jian

doi:10.3390/s21093140

Cited by 16 publications

(5 citation statements)

References 30 publications

(42 reference statements)

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“…Liu et al . (2021b) introduced the double precision gradient-based (DPG) method, as outlined in their work.…”

Section: Core Issues and Research Status In Dicmentioning

confidence: 99%

Review of research progress and development trend of digital image correlation

He,

Zhou,

Liu

et al. 2023

MMMS

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PurposeThe 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).Design/methodology/approachThe 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.FindingsThe 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.Originality/valueThis review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

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“…Liu et al . (2021b) introduced the double precision gradient-based (DPG) method, as outlined in their work.…”

Section: Core Issues and Research Status In Dicmentioning

confidence: 99%

Review of research progress and development trend of digital image correlation

He,

Zhou,

Liu

et al. 2023

MMMS

View full text Add to dashboard Cite

show abstract

“…The conventional DIC is a subset-based image matching method that determines the target location by comparing the correlation degree between the reference and deformed subsets [ 31 ]. It is notable that it has the limited convergence range of a rotation angle; this is a decorrelation problem that appears when the deformed image is subjected to large-scale rotation [ 32 ].…”

Section: The Modified Surf-enhanced Dic Algorithmmentioning

confidence: 99%

Damage Detection for Rotating Blades Using Digital Image Correlation with an AC-SURF Matching Algorithm

Liu

2022

Sensors

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The motion information of blades is a key reflection of the operation state of an entire wind turbine unit. However, the special structure and operation characteristics of rotating blades have become critical obstacles for existing contact vibration monitoring technology. Digital image correlation performs powerfully in non-contact, full-field measurements, and has increasingly become a popular method for solving the problem of rotating blade monitoring. Aiming at the problem of large-scale rotation matching for blades, this paper proposes a modified speeded-up robust features (SURF)-enhanced digital image correlation algorithm to extract the full-field deformation of blades. Combining an angle compensation (AC) strategy, the AC-SURF algorithm is developed to estimate the rotation angle. Then, an iterative process is presented to calculate the accurate rotation displacement. Subsequently, with reference to the initial state of rotation, the relative strain distribution caused by flaws is determined. Finally, the sensitivity of the strain is validated by comparing the three damage indicators including unbalanced rotational displacement, frequency change, and surface strain field. The performance of the proposed algorithm is verified by laboratory tests of blade damage detection and wind turbine model deformation monitoring. The study demonstrated that the proposed method provides an effective and robust solution for the operation status monitoring and damage detection of wind turbine blades. Furthermore, the strain-based damage detection algorithm is more advantageous in identifying cracks on rotating blades than one based on fluctuated displacement or frequency change.

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“…Carrying out the analysis of global motion information in video remains a challenging task due to the millions of pixels’ respective temporal vibration signal exiting in video. In engineering application areas and stereo-vision systems [ 51 , 52 , 53 , 54 , 55 , 56 , 57 ], the three-dimensional digital image correlation (3D DIC) and three-dimensional point tracking (3DPT) techniques are used to extract the full-field dynamic displacements of the analytical structure, and temporal vibration signals are further analyzed to obtain the material properties [ 58 , 59 ]. These methods are appropriate for structural engineering due to the law of mechanics; however, limitations arise when analyzing an irregular video.…”

Section: Spectrum-aware Video Magnificationmentioning

confidence: 99%

Bayesian-Inference Embedded Spline-Kerneled Chirplet Transform for Spectrum-Aware Motion Magnification

Cai

Lin

et al. 2022

Sensors

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The ability to discern subtle image changes over time is useful in applications such as product quality control, civil engineering structure evaluation, medical video analysis, music entertainment, and so on. However, tiny yet useful variations are often combined with large motions, which severely distorts current video amplification methods bounded by external constraints. This paper presents a novel use of spectra to make motion magnification robust to large movements. By exploiting spectra, artificial limitations and the magnification of small motions are avoided at similar frequency levels while ignoring large ones at distinct spectral pixels. To achieve this, this paper constructs spline-kerneled chirplet transform (SCT) into an empirical Bayesian paradigm that applies to the entire time series, giving powerful spectral resolution and robust performance to noise in nonstationary nonlinear signal analysis. The important advance reported is Bayesian-rule embedded SCT (BE-SCT); two numerical experiments show its superiority over current approaches. For applying to spectrum-aware motion magnification, an elaborate analytical framework is established that captures global motion, and use of the proposed BE-SCT for dynamic filtering enables a frequency-based motion isolation. Our approach is demonstrated on real-world and synthetic videos. This approach shows superior qualitative and quantitative results with less visual artifacts and more local details over the state-of-the-art methods.

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Subpixel Matching Using Double-Precision Gradient-Based Method for Digital Image Correlation

Cited by 16 publications

References 30 publications

Review of research progress and development trend of digital image correlation

Review of research progress and development trend of digital image correlation

Damage Detection for Rotating Blades Using Digital Image Correlation with an AC-SURF Matching Algorithm

Bayesian-Inference Embedded Spline-Kerneled Chirplet Transform for Spectrum-Aware Motion Magnification

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