Search Results (279)

To overcome the complexity of yarn color measurement using spectrophotometry with yarn winding techniques and to enhance consistency with human visual perception, a yarn color measurement method based on digital photography is proposed. This study employs a photographic colorimetry system to capture digital images of single yarns. The yarn and background are segmented using the K-means clustering algorithm, and the centerline of the yarn is extracted using a skeletonization algorithm. Spectral reconstruction and colorimetric principles are then applied to calculate the color values of pixels along the centerline. Considering the nonlinear characteristics of human brightness perception, the final yarn color is obtained through a nonlinear texture-adaptive weighted computation. The method is validated through psychophysical experiments using six yarns of different colors and compared with spectrophotometry and five other photographic measurement methods. Results indicate that among the seven yarn color measurement methods, including spectrophotometry, the proposed method—based on centerline extraction and nonlinear texture-adaptive weighting—yields results that more closely align with actual visual perception. Furthermore, among the six photographic measurement methods, the proposed method produces most similar to those obtained using spectrophotometry. This study demonstrates the inconsistency between spectrophotometric measurements and human visual perception of yarn color and provides methodological support for developing visually consistent color measurement methods for textured textiles. Full article

Dynamic impact experiments based on high-speed photography and digital image correlation (DIC) techniques were carried out on sandstone specimens containing arched holes to investigate the effect of the incident angle. In addition, the complex function method based on conformal mapping was used to theoretically calculate the transient dynamic stress distributions around the arched holes. The test results indicated that the strength and modulus of elasticity of the specimens under dynamic impact decreased and then increased with the increase of the inclination angle of the holes from 0 to 90° at intervals of 15°, reaching a minimum value at 60°, due to the large stress concentration at this angle leading to the shear failure of the specimen. During the experiment, rock debris ejections, spalling, and heaving were observed around the holes, and the rock debris ejections served as an indicator to identify the early fracture. The damage mechanism around the holes was revealed theoretically, i.e., the considerable compressive stress concentration in the perpendicular incidence direction around the arched hole and the tensile stress concentration on the incidence side led to the initiation of the damage around the cavity, and the theoretical results were in satisfactory agreement with the experimental results. In addition, the effect of the initial stress on the dynamic response of the arched tunnel was discussed. Full article

The rapid urbanization and technological advancements in the United Arab Emirates (UAE) have placed its modern architectural heritage from the 1970s and 1980s at increasing risk of being unrecognized and lost, particularly in Dubai following the discovery of oil. This research addresses the critical need for the documentation and heritage representation of Dubai’s modern heritage, a city undergoing rapid transformation within a globalized urban landscape. Focusing on the Nasser Rashid Lootah Building (Toyota Building), an iconic early 1970s residential high-rise representing the modern architecture of Dubai and a significant milestone in its architectural history, this study explores a replicable and cost-effective approach to digitally document and conserve urban heritage under threat. The existing building was meticulously documented and analyzed to highlight its enduring value within the fast-changing urban fabric. Through the innovative combination of drone photography, ground-based photography, and HBIM, a high-resolution 3D model and a semantically organized HBIM prototype were generated. This research demonstrates a replicable measure for identifying architectural values, understanding modernist design typologies, and raising local community awareness about Dubai’s modern heritage. Ultimately, this study contributes toward developing recognition criteria and guiding efforts in documenting modern high-rise buildings as vital heritage worthy of recognition, documentation, and future conservation in the UAE. Full article

Background: Digital dental photography is increasingly essential for documentation and smile design. This study aimed to compare the linear measurement accuracy of various smartphones and a Digital Single-Lens Reflex (DSLR) camera against digital models obtained by intraoral and desktop scanners. Methods: Tooth height and width from six different casts were measured and compared using images acquired with a Canon EOS 250D DSLR, six smartphone models (iPhone 13, iPhone 15, Samsung Galaxy S22 Ultra, Samsung Galaxy S23 Ultra, Samsung Galaxy S24, and Vivo T2), and digital scans obtained from the Helios 500 intraoral scanner and the Ceramill Map 600 desktop scanner. All image measurements were performed using ImageJ software (National Institutes of Health, Bethesda, MD, USA), and statistical analysis was conducted using one-way analysis of variance (ANOVA) with Tukey’s post hoc test (α = 0.05). Results: The results showed no significant differences in measurements across most imaging methods (p > 0.05), except for the Vivo T2, which showed a significant deviation (p < 0.05). The other smartphones produced measurements comparable to those of the DSLR, even at distances as close as 16 cm. Conclusions: These findings preliminary support the clinical use of smartphones for accurate dental documentation and two-dimensional smile design, including the posterior areas, and challenge the previously recommended 24 cm minimum distance for mobile dental photography (MDP). This provides clinicians with a simplified and accessible alternative for high-accuracy dental imaging, advancing the everyday use of MDP in clinical practice. Full article

Video stabilization is a critical technology for enhancing video quality by eliminating or reducing image instability caused by camera shake, thereby improving the visual viewing experience. It has deeply integrated into diverse applications—including handheld recording, UAV aerial photography, and vehicle-mounted surveillance. Propelled by advances in deep learning, data-driven stabilization methods have emerged as prominent solutions, demonstrating superior efficacy in handling jitter while achieving enhanced processing efficiency. This review systematically examines the field of video stabilization. First, this paper delineates the paradigm shift from classical to deep learning-based approaches. Subsequently, it elucidates conventional digital stabilization frameworks and their deep learning counterparts along with establishing standardized assessment metrics and benchmark datasets for comparative analysis. Finally, this review addresses critical challenges such as robustness limitations in complex motion scenarios and latency constraints in real-time processing. By integrating interdisciplinary perspectives, this work provides scholars with academically rigorous and practically relevant insights to advance video stabilization research. Full article

As humans continue to develop the undersea engineering ecosystem of systems, the consequences of catastrophic events must continue to be investigated and understood. Almost every undersea pressure vessel, from pipelines to sensors to unmanned vehicles, has the potential to experience a catastrophic collapse, known as an implosion. This collapse can be caused by hydrostatic pressure or any combination of external loadings from natural disasters to pressure waves imparted by other implosion or explosion events. During an implosion, high-magnitude pressure waves can be emitted, which can cause adverse effects on surrounding structures, marine life, or even people. The imploding structure, known as an implodable volume, can be in a free-field or confined environment. Confined implosion is characterized by a surrounding structure that significantly affects the flow of fluid around the implodable volume. Often, the confining structure is cylindrical, with one closed end and one open end. This work seeks to understand the effect of fluid flow restriction on the physics of implosion inside a confining tube. To do so, a comprehensive experimental study is conducted using a unique experimental facility. Thin-walled aluminum cylinders are collapsed inside a confining tube within a large pressure vessel. High-speed photography and 3D Digital Image Correlation are used to gather structural displacement and velocities during the event while an array of dynamic pressure sensors capture the pressure data inside the confining tube. The results of this work show that by changing the size of the open end, referred to as the flow area ratio, there can be a significant effect on the structural deformations and implosion severity. It also reveals that only certain configurations of holes at the open end of the tube play a role in the dynamic pressure pulse measured at the closed end of the tube. By understanding the consequences of an implosion, designers can make decisions about where these pressure vessels should be in relation to other pressure vessels, critical infrastructure, marine life, or people. In the same way that engineers design for earthquakes and analyze the impact their structures have on the environment around them, contributors to the undersea engineering ecosystem should design with implosion in mind. Full article

This study examines the evolving relationship between online media coverage and protest movements by analyzing year-long demonstrations in Israel against Prime Minister Benjamin Netanyahu. Through comprehensive qualitative thematic analysis and content analyses of 219 online newspaper articles from five major Israeli newspapers; 324 social media posts across Facebook, Instagram, and Twitter; and 9 semi-structured interviews with protest leaders, this research identifies a gradual paradigm shift in protest representation in online media. The findings reveal a transition from the traditional “protest paradigm”—which frames protests as violent and remote through warlike discourse and visual distancing—toward an emerging “our protest paradigm”, characterized by rhetorical and visual proximity to protesters. This new paradigm manifests through personal testimonies in mainstream media and portrait photography on social media platforms, both creating a sense of closeness and accountability. The study further reveals a significant disconnect between protest leaders’ perceptions and legacy media, as leaders increasingly view traditional media as irrelevant despite their advisers’ recommendations to engage with it. Using polysystem theory as a theoretical framework, this research demonstrates how two media systems—legacy media and social media—operate with epistemological rigidity, challenging the previously established notion of “competitive symbiosis” between protesters and journalists. This investigation offers a novel analytical perspective through the lens of distance, illuminating how changing dynamics in online information transfer are reshaping protest coverage and production. The resulting paradigm model explains the coexistence of two simultaneous protest paradigms and provides valuable insights into the contemporary relationship between social movements, legacy media, and digital platforms in an evolving media ecosystem. Full article

In the central Mesa Verde region, rock art occurs on canyon walls and on boulders that are frequently associated with other archaeological remains. Moreover, rock art, together with architecture and pottery, is actually a primary source of archaeological information about the presence of various cultures in the area. It includes paintings and petroglyphs of Ancestral Pueblo farming communities, images and inscriptions made by post-contact Ute and possibly Diné (Navajo) people as well as historical inscriptions of the early Euro-Americans in this area. This paper presents the results of archaeological investigations at four large rock art sites from Sandstone Canyon, southwestern Colorado, within the Canyons of the Ancients National Monument (CANM). Methods of rock art recording included advanced digital photography, photogrammetry, terrestrial laser scanning (TLS), hand tracing, and consultations with members of indigenous societies and rock art scholars. Geophysics and sondage excavations were conducted at one site revealed important information about archaeology, environment, and geology of the area. Analysis of rock art and other material evidence aims to help reconstruct and understand the mechanisms and nature of cultural changes, migrations, and human–environmental interactions and later cross-cultural contacts between indigenous peoples and Anglo-American ranchers and settlers in southwestern Colorado and the US Southwest. Full article

The precise identification and classification of tree species in young forests during their early development stages are vital for forest management and silvicultural efforts that support their growth and renewal. However, achieving accurate geolocation and species classification through field-based surveys is often a labor-intensive and complicated task. Remote sensing technologies combined with machine learning techniques present an encouraging solution, offering a more efficient alternative to conventional field-based methods. This study aimed to detect and classify young forest tree species using remote sensing imagery and machine learning techniques. The study mainly involved two different objectives: first, tree species detection using the latest version of You Only Look Once (YOLOv12), and second, semantic segmentation (classification) using random forest, Categorical Boosting (CatBoost), and a Convolutional Neural Network (CNN). To the best of our knowledge, this marks the first exploration utilizing YOLOv12 for tree species identification, along with the study that integrates digital aerial photogrammetry with Planet imagery to achieve semantic segmentation in young forests. The study used two remote sensing datasets: RGB imagery from unmanned aerial vehicle (UAV) ortho photography and RGB-NIR from PlanetScope. For YOLOv12-based tree species detection, only RGB from ortho photography was used, while semantic segmentation was performed with three sets of data: (1) Ortho RGB (3 bands), (2) Ortho RGB + canopy height model (CHM) + Planet RGB-NIR (8 bands), and (3) ortho RGB + CHM + Planet RGB-NIR + 12 vegetation indices (20 bands). With three models applied to these datasets, nine machine learning models were trained and tested using 57 images (1024 × 1024 pixels) and their corresponding mask tiles. The YOLOv12 model achieved 79% overall accuracy, with Scots pine performing best (precision: 97%, recall: 92%, mAP50: 97%, mAP75: 80%) and Norway spruce showing slightly lower accuracy (precision: 94%, recall: 82%, mAP50: 90%, mAP75: 71%). For semantic segmentation, the CatBoost model with 20 bands outperformed other models, achieving 85% accuracy, 80% Kappa, and 81% MCC, with CHM, EVI, NIRPlanet, GreenPlanet, NDGI, GNDVI, and NDVI being the most influential variables. These results indicate that a simple boosting model like CatBoost can outperform more complex CNNs for semantic segmentation in young forests. Full article

An absolutely conflicting value for the incorporation of the Lode parameter into a fracture criterion was reported in the literature when predicting the ballistic resistance of metallic plates failing through shear plugging. In this study, a combined experimental–numerical investigation was conducted to understand the dynamic shear fracture behavior under compression–shear stress states. Flat-hat-shaped specimens of 30CrMnSiNi2A high-strength steel were loaded using a Split Hopkinson Pressure Bar apparatus, combining the ultra-high-speed photography technique, digital image correlation method, and microstructure observation. Parallel finite element simulations were performed using both a modified Johnson–Cook (MJC) fracture criterion or an extended Xue–Wierzbicki (EXW) fracture criterion with Lode dependence to reveal the value of the Lode parameter incorporation. It was found that deformed shear bands with a width of approximately 0.14 mm form at a critical impact velocity. The EXW criterion correctly predicts the critical fracture velocity and estimates the fracture initiation instants within an error of 5.3%, whereas the MJC fracture criterion overestimates the velocity by 14.3%. Detailed analysis shows that the EXW criterion predicts a combined failure mechanism involving ductile fracture and material instability, while the MJC fracture criterion attributes the failure exclusively to material instability. The improved accuracy achieved by employing the Lode-dependent EXW fracture criterion may be attributed to the compression–shear stress state and the accurate prediction of the failure mechanism of the dynamic shear fracture. Full article

Folk art includes objects that are items for everyday use and, at the same time, gracefully reflect the Greek artistic point of view, drawing its inspiration from life itself, the environment and its beauties, and local tradition. An 18th c. wood-carved and painted chest coming from the famous wood-carved centers of Epirus in Greece is presented in this study. As the number of studies and the general bibliographical references are limited for these kinds of items, prior to interventive conservation, a protocol of analysis was followed to identify the damages, the construction materials, and previous alterations. The main goal of this study is to identify the component materials using non-destructive techniques. The methodology followed for the documentation of the artifact includes the following: a. digital microscopy to identify damage from insects, different cracks and losses on the gesso and paint surface, corrosion products, etc.; b. 3D imaging using a polycam, with special attention given to the inside decoration of the cap; c. IR and UV photography to identify any previous alterations or signs of alterations in the varnish layers; d. and XRF analysis to identify the three (3) main colors of the chest, such as the blue used extensively as a background, red, and white. Nevertheless, the Greek folklore painting palette is limited, and for this reason, this study can be a foundation for research on similar artifacts. Full article

Accurately monitoring forest canopy height is crucial for sustainable forest management, particularly in southeastern North Carolina, USA, where dense forests and limited accessibility pose substantial challenges. This study presents an explainable machine learning framework that integrates sparse GEDI LiDAR samples with multi-sensor remote sensing data to improve both the accuracy and interpretability of forest canopy height estimation. This framework incorporates multitemporal optical observations from Sentinel-2; C-band backscatter and InSAR coherence from Sentinel-1; quad-polarization L-Band backscatter and polarimetric decompositions from the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR); texture features from the National Agriculture Imagery Program (NAIP) aerial photography; and topographic data derived from an airborne LiDAR-based digital elevation model. We evaluated four machine learning algorithms, K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), and eXtreme gradient boosting (XGB), and found consistent accuracy across all models. Our evaluation highlights our method’s robustness, evidenced by closely matched R² and RMSE values across models: KNN (R² of 0.496, RMSE of 5.13 m), RF (R² of 0.510, RMSE of 5.06 m), SVM (R² of 0.544, RMSE of 4.88 m), and XGB (R² of 0.548, RMSE of 4.85 m). The integration of comprehensive feature sets, as opposed to subsets, yielded better results, underscoring the value of using multisource remotely sensed data. Crucially, SHapley Additive exPlanations (SHAP) revealed the multi-seasonal red-edge spectral bands of Sentinel-2 as dominant predictors across models, while volume scattering from UAVSAR emerged as a key driver in tree-based algorithms. This study underscores the complementary nature of multi-sensor data and highlights the interpretability of our models. By offering spatially continuous, high-quality canopy height estimates, this cost-effective, data-driven approach advances large-scale forest management and environmental monitoring, paving the way for improved decision-making and conservation strategies. Full article

Digital repeat photography is currently applied mainly in geophysical studies of ecosystems. However, its role as a tool that can be utilized in conventional phenology, tracking a plant’s seasonal developmental cycle, is growing. This study’s main goal was to develop an easy-to-reproduce, single-camera-based novel approach to determine the flowering phases of 12 woody plants of various deciduous species. Field observations served as binary class calibration datasets (flowering and non-flowering stages). All the image RGB parameters, designated for each plant separately, were used as plant features for the models’ parametrization. The training data were subjected to various transformations to achieve the best classifications using the weighted k-nearest neighbors algorithm. The developed models enabled the flowering classifications at the 0, 1, 2, 3, and 5 onset day shift (absolute values) for 2, 3, 3, 2, and 2 plants, respectively. For 9 plants, the presented method enabled the flowering duration estimation, which is a valuable yet rarely used parameter in conventional phenological studies. We found the presented method suitable for various plants, despite their petal color and flower size, until there is a considerable change in the crown color during the flowering stage. Full article

Painted surfaces, regardless of their substrate, possess unique elements crucial for their study and interpretation. These elements include geometric characteristics, surface texture, brushwork relief, color layer morphology, and preservation state indicators like overpainting, interventions, cracks, and mechanical deformations. Traditional recording methods such as handwritten or digital descriptions, 2D scale drawings, calipers, rulers, tape measures, sketches, tracings, and conventional or technical photography fall short in capturing the three-dimensional detail necessary for comprehensive analysis. To overcome these limitations, this paper proposes the integration of two digital tools, Close-Range Photogrammetry (SfM-MVS) and Reflectance Transformation Imaging (RTI), which have become accessible with the advancement of computing power. While other 3D imaging tools like laser scanners and structured light systems exist and may be preferred for very specialized applications, such as capturing the texture of the surface with sub-millimeter accuracy, SfM-MVS and RTI offer a cost-efficient and highly accurate alternative, with 3D modeling capabilities and advanced pixel color fidelity, essential for documenting the geometric and color details of painted artifacts. The application of these highly promising methods to the mural paintings from the Palace of Tiryns (Nafplion, Greece) demonstrates their potential, providing significant insights for art historians, researchers, conservators, and curators. Full article

Background/Objectives: Clinical photography is an essential component of orthodontic records, alongside radiographs, dental scanners, and cone beam computed tomography. However, neither the American Association of Orthodontists nor the Spanish Society of Orthodontics provides a standardized protocol for dental photography. This study aimed to evaluate the current practices, challenges, and training needs related to clinical photography among orthodontists in Spain. Methods: A cross-sectional survey was designed using Google Forms^® and distributed to orthodontists practising in Spain. A sample size of 303 participants was calculated (95% confidence level; 0.1 precision). The questionnaire covered photographic practices, equipment usage, self-assessed skills, interest in training, and legal considerations. Descriptive and inferential analyses were performed using R software (significance level 0.05; version 4.4.1). Results: A total of 304 valid responses were analyzed, with a predominance of female participants (77.96%) and a mean age of 37.54 years (SD: 9.08). Digital single-lens reflex (DSLR) cameras with macro lenses and ring flashes were the most used equipment (68.09%). The primary software for cropping and editing images were Windows Photos (28.95%) and MacOS Photos (16.12%). Male participants rated their photography skills higher than female participants (p = 0.003), and those with full-time orthodontic training considered their skills better than those with other types of training (p = 0.014). Photography was most valued for diagnosis in the exclusive orthodontics group (p = 0.019). Additionally, 75.99% of respondents expressed interest in improving their photography skills through specialized courses. Conclusions: This study highlights significant variability in photographic practices among orthodontists in Spain. The findings emphasize the need for standardized photography protocols to enhance diagnostic accuracy, clinical documentation, and professional training. Full article