Search Results (2,168)

Source camera identification on smartphones constitutes a fundamental task in multimedia forensics, providing essential support for applications such as image copyright protection, illegal content tracking, and digital evidence verification. Numerous techniques have been developed for this task over the past decades. Among existing approaches, Photo-Response Non-Uniformity (PRNU) has been widely recognized as a reliable device-specific fingerprint and has demonstrated remarkable performance in real-world applications. Nevertheless, the rapid advancement of computational photography technologies has introduced significant challenges: modern devices often exhibit anomalous behaviors under PRNU-based analysis. For instance, images captured by different devices may exhibit unexpected correlations, while images captured by the same device can vary substantially in their PRNU patterns. Current approaches are incapable of automatically exploring the underlying causes of these anomalous behaviors. To address this limitation, we propose a simple yet effective forensic analysis framework leveraging Exchangeable Image File Format (EXIF) metadata. Specifically, we represent EXIF metadata as type-aware word embeddings to preserve contextual information across tags. This design enables visual interpretation of the model’s decision-making process and provides complementary insights for identifying the anomalous behaviors observed in modern devices. Extensive experiments conducted on three public benchmark datasets demonstrate that the proposed method not only achieves state-of-the-art performance for source camera identification but also provides valuable insights into anomalous device behaviors. Full article

This article presents a novel framework for encrypting color images to enhance digital data security using deep learning and artificial intelligence techniques. The system employs a two-model neural architecture: the first, a Convolutional Neural Network (CNN), verifies sender authenticity during user authentication, while the second extracts unique fingerprint features. These features are converted into high-entropy encryption keys using Particle Swarm Optimization (PSO), minimizing key similarity and ensuring that no key is reused or transmitted. Keys are generated in real time simultaneously at both the sender and receiver ends, preventing interception or leakage and providing maximum confidentiality. Encrypted images are secured using the Advanced Encryption Standard (AES-256) with keys uniquely bound to each user’s biometric identity, ensuring personalized privacy. Evaluation using security and encryption metrics yielded strong results: entropy of 7.9991, correlation coefficient below 0.00001, NPCR of 99.66%, UACI of 33.9069%, and key space of 2²⁵⁶. Although the final encryption employs an AES-256 key (key space of 2²⁵⁶), this key is derived from a much larger deep-key space of 2⁸¹⁹² generated by multi-layer neural feature extraction and optimized via PSO, thereby significantly enhancing the overall cryptographic strength. The system also demonstrated robustness against common attacks, including noise and cropping, while maintaining recoverable original content. Furthermore, the neural models achieved classification accuracy exceeding 99.83% with an error rate below 0.05%, confirming the framework’s reliability and practical applicability. This approach provides a secure, dynamic, and efficient image encryption paradigm, combining biometric authentication and AI-based feature extraction for advanced cybersecurity applications. Full article

This research work addresses the mechanical and metallurgical characterisation, as well as the failure features, of two types of lap-fillet autogenous laser-welded joints made of ultra-thin sheets by applying an appropriate welding technology for producing sound welds and flawless joints. Both welded samples, one made only of stainless steel (SS-SS) sheets, and the other made of stainless steel and carbon steel (SS-CS) plates, were subjected to tensile–shear loads that are representative of the in-service conditions. The experimental research was focused on determining, by the digital image correlation (VIC-2D) method, the strain field and the rotation angle of the welded joints that were developed during loading tests of the welded specimens. Comparing to the classical testing method applied to study the joint overall mechanical properties, the novelty of this research consists of local mechanical behaviour assessment of relevant zones from similar and dissimilar welded joints, by using the innovative technique VIC-2D. Based on the analysis of the experimental results, it was found that the maximum rotation angle is 2.5 times higher in the SS-SS similar welded joint, in comparison with the SS-CS dissimilar welded joint. Despite this finding, the SS-CS specimen failed in the CS base material, far from the weld, with the failure phenomenon being preceded by the material yielding and necking. This failure mode is consistent with the detected strength mismatch of the SS-CS joint, with respect to the CS base material. In contrast, the quasi-ductile fracture of the SS-SS welded joint occurred by plastic exhaustion at the boundary between the narrow Heat-Affected Zone (HAZ) of SS and the Fuzion Zone (FZ). These outcomes are consistent with the hardness profile, microstructural heterogeneities found in the lap-fillet welded joints, and the load versus elongation curves that are determined and discussed in this paper. This research provides new insight and original information on the materials’ response to the autogenous laser welding, which will contribute to improving the knowledge on the ultra-thin lap-fillet welded similar and dissimilar steels. Full article

Adiabatic shear banding (ASB) is a critical failure mechanism in titanium alloys subjected to high-strain-rate deformation, and its initiation is strongly influenced by the initial crystallographic texture. The dynamic response and ASB sensitivity of extruded and annealed Ti-6Al-4V (TC4) alloy rods were investigated under dynamic compression of cubic specimens along the extrusion direction (ED) and the transverse direction (TD) at a strain rate of 2500 s⁻¹. Split Hopkinson pressure bar (SHPB) tests combined with digital image correlation (DIC) were employed to obtain the stress–strain response and the evolution of strain localization. A dislocation density-based crystal plasticity finite element model (CPFEM), incorporating the measured texture, was established to elucidate the correlation between texture and ASB behavior. The experimental results show that TD specimens exhibit a yield strength approximately 100 MPa higher than that of ED specimens, while both orientations display comparable post-yield hardening behavior. ASB initiation occurs earlier in TD (compressive strain ~0.13) than in ED (~0.23), indicating greater ASB sensitivity in the TD orientation. The CPFEM successfully reproduces the directional stress–strain responses and the observed localization morphology, enabling mechanistic interpretation in terms of slip activity and thermomechanical coupling. The simulations indicate that ED loading is dominated by prismatic ⟨a⟩ slip, resulting in lower flow stress and more dispersed strain localization. In contrast, TD loading is governed primarily by pyramidal ⟨c + a⟩ slip, leading to elevated flow stress and intensified localization. The higher ASB sensitivity in the TD orientation is therefore attributed to texture-controlled slip-mode partitioning, enhanced thermomechanical coupling, and a more concentrated crystallographic orientation distribution that facilitates intergranular slip transfer. These findings provide guidance for tailoring microtexture to mitigate dynamic failure in titanium alloys subjected to high-strain-rate loading. Full article

Background/Objectives: Dental implants are an established modality for oral rehabilitation, but their biomechanical success depends on controlling peri-implant strain, which is influenced by implant angulation, splinting, and length. This in vitro study evaluated the effects of these variables on strain and displacement under axial and oblique loading using digital image correlation (DIC). Methods: Three CBCT-derived mandibular models were 3D-printed and restored with screw-retained full-metal crowns. Group 1 compared parallel vs. angulated implants; Group 2 assessed splinted vs. non-splinted restorations; and Group 3 compared short (4.2 × 6.25 mm) vs. long (4.2 × 13 mm) implants. All specimens were loaded to 500 N at 0°, 15°, and 30° using a universal testing machine. Strain and displacement were analyzed with Istra 4D software and statistically evaluated using ANOVA and independent t-tests (α = 0.05). Results: Parallel implants exhibited progressively higher strain with load angle, peaking at 30° (p < 0.01), while angulated implants recorded their highest strain at 0° (p = 0.008), indicating better adaptation to oblique forces. Splinted restorations significantly reduced strain at 0° and 30° (p = 0.023) and lowered displacement across all inclinations (p = 0.0001). Short implants consistently produced greater strain and displacement than long implants (p < 0.02). Conclusions: Angulated implants mitigated strain under off-axis loading compared to parallel configurations. Splinting decreased strain and displacement, while longer implants consistently improved biomechanical performance. Optimal selection of implant orientation, splinting, and length may minimize peri-implant strain under functional loads. Findings are limited to in vitro conditions with static loading and a single implant system. Full article

This research investigated the feasibility of 3D-printed external fixator (EF) rings made from carbon fiber reinforced polyamide 6 (PA6-CF) as an alternative to the conventional metallic counterpart. The study integrated tensile testing with digital image correlation (DIC) in as-printed and cold plasma-sterilized conditions, finite-element analysis (FEA) under wire loading, topology optimization for material and energy reduction, and evaluation of printability limits for large PA6-CF rings. The average Young’s modulus was 4.76 GPa and the maximum tensile strength was 60.5 MPa for as-printed samples, decreasing by 6.4% and 10.4% after sterilization, respectively. Using these properties as model inputs, FEA predicted safety factors larger than 1.42 for all configurations under 1000 N wire pretension, while topology optimization targeted up to 50% mass reduction without compromising ring stiffness. The study also revealed challenges in the printability of PA6-CF for large and thin components, including dimensional contraction, significant warping and moisture-induced defects, requiring an experienced 3D printer operator. Full article

Digital image-based determination of aggregate and rock gradation has been only limitedly addressed in the existing literature despite its considerable potential to transform conventional material characterization practices in civil engineering. Rapid and accurate estimation of aggregate and rock particle size distributions using advanced image-based analytical methods can significantly improve efficiency, consistency, and scalability in design, construction, and quality control processes, particularly in large-scale structural and geotechnical engineering projects where traditional sieve analysis is time-consuming, labor-intensive, and difficult to apply under field conditions. In this study, an image-based methodology is proposed to rapidly detect aggregate particles and determine their size-based proportions within a pile by employing image enhancement, segmentation, and boundary detection algorithms. The results obtained from digital image processing are comparatively evaluated against experimental sieve analysis data, demonstrating a strong correlation between the two approaches. Low RMSE values achieved for larger aggregate sizes, such as 25.4 mm and 19 mm, indicate high detection accuracy, while the relatively higher yet acceptable RMSE values obtained for smaller particles, including 12.7 mm and 9.5 mm, confirm that the method maintains practical sensitivity across different size ranges. By analyzing samples collected from various aggregate and rock piles, the study further demonstrates the originality, robustness, and effectiveness of the proposed approach in evaluating heterogeneous material groups. Overall, the findings highlight that digital image-based determination offers a fast, reproducible, and non-destructive alternative to traditional sieve analysis, making it particularly valuable for reinforced concrete aggregate assessment and port fill rock characterization in large-scale structural and geotechnical engineering applications. Full article

Feline nasal carcinomas are rare but clinically aggressive neoplasms. This study characterizes their histopathological features and evaluates HER2, p53, Ki-67, and PCNA expression using immunohistochemistry and digital image analysis, aiming to provide a comprehensive biological characterization with potential prognostic and therapeutic implications. Tumors were classified into adenocarcinomas (AC) and non-adenocarcinomas (non-AC). Among the 23 cases examined, adenocarcinoma was the most common subtype (17 cases). HER2 was scored as 3+ in 7 cases, 2+ in 8 cases, 1+ in 5 cases, and 3 cases were scored 0. A statistically significant association was found between histological type and HER2 expression (Fisher’s exact test, p = 0.02), with a higher prevalence of HER2 positivity in adenocarcinomas. Evaluation of p53 expression according to histological grouping showed a trend toward significance (p = 0.0593), with p53 positivity observed exclusively in non-AC. The Ki-67 index had a median of 4.4 (min 0.5, max 21.06), and the PCNA index had a median of 82.26 (min 19.55, max 100). No significant associations were identified between the Ki-67 labeling index and HER2 expression, histotype, and the inflammatory infiltrate. Finally, Pearson correlation analysis revealed no significant correlation between Ki-67 and PCNA indices (p = 0.32). The overexpression of HER2 lays the groundwork for the possible use of anti-HER2 targeted drugs in this tumor type, particularly in adenocarcinomas. These findings provide baseline immunohistochemical data for feline nasal carcinomas and highlight HER2 as a relevant biomarker for future diagnostic and therapeutic research. Full article

Amidst rapid urbanization and modernization, numerous traditional villages in China face severe challenges, including landscape homogenization and the erosion of their distinctive characteristics. Addressing this issue requires a method capable of systematically identifying, analyzing, and reconstructing both the landscape and its underlying cultural features. This study proposes a digital analytical approach that integrates multimodal artificial intelligence with landscape language theory to address the homogenization of cultural landscapes in traditional Chinese villages. Taking Xinye Village in Zhejiang Province as a case study, the research systematically decodes its landscape spatial narratives and underlying cultural genes. This framework systematically deconstructs village landscapes across four levels: “vocabulary, context, grammar, and semantics”. The village image database is first automatically recognized and statistically analyzed by computer vision technology, which extracts 31 core landscape vocabulary items from three main categories and nine subcategories. Second, Retrieval-augmented Generation technology is employed to synthesize from the constructed domain-specific corpus, a natural context structured around Yuhua Mountain and Daofeng Mountain, as well as a cultural context based on ancestral hall order, connected through folk activities, and idealized by farming and reading passed down through generations. Building on this framework, a multimodal model was used to examine the spatial composition and combinatorial laws of landscape features. Six essential dimensions—spatial layout, visual order, element combination, functional relationships, circulation layout, and scale correlations—revealed the spatial grammar of shuikou landscape. Lastly, the semantic values conveyed by the landscape vocabulary were thoroughly analyzed across three dimensions—form, function, and culture—by integrating a knowledge base. This work creates a landscape language atlas of Xinye Village by combining these studies and using a linguistic model of “character-word-sentence-paragraph”. By methodically deciphering the clan’s cultural code of “farming and reading passed down through generations”, this clearly reconstructs the spatial narrative logic from micro-elements to macro-patterns. This research not only advances the study of landscape language in traditional villages from qualitative description toward a systematic, digital, and interpretable paradigm but also provides an operational theoretical and methodological foundation for the in-depth interpretation, conservation, and transmission of traditional village cultural landscapes. Full article

During fatigue tests of tidal turbine blades, digital image correlation (DIC) is used to collect vital information about the specimen. DIC provides high-resolution displacement and strain maps of selected blade sections; however, continuous operation is hindered by the need to acquire, transfer, and process large volumes of high-resolution images, precluding real-time use during long tests. We address this problem by optimising sparse sensing locations on the blade surface so that full-field maps can be accurately reconstructed from a small subset of pixel measurements. In contrast to most DIC improvements found in the literature, which focus on accelerating the processing stage, this approach circumvents the need to collect high-resolution data. We evaluate this approach in a case study at FastBlade, a dedicated testing facility for tidal turbine blades. With less than 1% of the original pixels measured, the mean relative error evaluated on the dataset is 0.4% and 16% for displacement and strain maps, respectively, with the larger strain error reflecting the higher spatial complexity of strain fields. The optimised layouts outperform random and grid-like arrangements. The framework enables real-time monitoring and, subject to relevant validation, might be applied to reconstruct high-resolution strain maps directly from strain-gauge readings, potentially extending to in-ocean blade monitoring. Given the high accuracy of deflection reconstructions, using them to derive strain fields is suggested as a direction for further study. Full article

Objectives: To provide a mechanism-oriented integration of clinical and biomechanical evidence regarding fixation failure in fifth metatarsal fractures, with particular emphasis on Jones and diaphyseal stress fractures, and to clarify the mechanical determinants that influence construct performance under physiologic gait-related loading. Methods: A narrative, concept-driven review was conducted focusing on experimental biomechanical investigations and clinically relevant outcome studies addressing cyclic shear, bending, torsion, interfragmentary gap behavior, and loading direction. Special attention was given to studies employing advanced experimental models, including three-dimensional printed anatomical constructs combined with digital image correlation (DIC), to evaluate fixation strategies under simulated gait-phase loading conditions. Literature selection was guided by thematic relevance to construct mechanics and clinical fixation outcomes rather than systematic retrieval criteria. Results: Available evidence indicates that fixation constructs relying predominantly on interfragmentary compression demonstrate increased sensitivity to imperfect reduction, interfragmentary gaps, and multidirectional cyclic shear forces, particularly during midstance loading. Experimental models suggest that loading angle and gap size significantly influence stress concentration and failure patterns. Plate-based and hybrid constructs may provide improved resistance to cyclic bending and shear in specific experimental conditions, maintain stability in the presence of small fracture gaps, and distribute mechanical loads more uniformly across the fracture site. These biomechanical characteristics may help explain reported clinical patterns of delayed union, refracture, and hardware failure in high-demand patients or in cases with cortical compromise. Conclusions: Fixation failure in fifth metatarsal fractures appears to result from the interaction between fracture morphology, patient-specific loading demands, and construct biomechanics. Mechanism-based integration of biomechanical findings with clinical context may support individualized surgical decision-making. However, given the heterogeneity of available clinical data and the inherent limitations of experimental models, biomechanical insights should be interpreted as hypothesis-generating and complementary to clinical judgment rather than prescriptive guidance. Full article

Background/Objectives: Osseointegration is essential for the long-term success of dental implants, and radiographic assessment may support the evaluation of peri-implant bone healing. This retrospective study evaluated peri-implant radiographic bone density (PIBD) as a potential indicator of osseointegration in patients who underwent successful implant-prosthetic rehabilitation. Methods: Patients with at least one endosseous dental implant and a minimum of two standardized periapical radiographs—one at placement (T0) and one during follow-up—were included. Digital radiographs were obtained using the paralleling technique and analyzed with ImageJ^®. Normalized bone density values were calculated for predefined areas of interest (AOIs). Marginal Bone Level (MBL) changes were also assessed. Statistical analyses included the Shapiro–Wilk test, Kruskal–Wallis test, and Dunn’s post hoc test with Bonferroni correction. Results: 88 implants in 64 patients were analyzed (198 radiographs; 1299 AOIs measurements). Normalized bone density showed significant temporal changes in several AOIs, mainly from 3 to 12 months, across coronal/middle/apical regions. PIBD decreased by approximately 8% between T0 and 3 months, followed by a significant increase at one year. MBL values were minimal and well below physiologic thresholds throughout follow-up. No significant correlation was found between MBL and normalized bone density. Conclusions: PIBD assessment may be a reliable, non-invasive tool for monitoring osseointegration during follow-up and supporting clinical decision-making in postoperative controls. The temporal pattern observed confirms three radiographic healing phases after implant placement: an initial decrease in PIBD during early remodeling, a subsequent increase reflecting osseointegration, and a final stabilization phase corresponding to tertiary implant stability. Full article

The use of high-performance concrete is a common practice in the construction of large-span bridges, where creep deformation may exert a considerable influence. This article puts forth a practical calculation method for long-term creep deformation of concrete bridges, based on short-term laboratory creep tests and multi-factor modification methods. A case study of a large-span railway concrete cable-stayed bridge examines the prediction results in conjunction with the monitoring data derived from digital image correlation (DIC) and compares these with the existing specifications. The results demonstrate that the mid-span deflection predicted by the proposed model shows a high degree of agreement with the short-term measurements. Over a monitoring period of 247 days, the mean mid-span deflection is found to be 2.948 mm and the predicted value is 3.343 mm, giving a relative error of 11.8% relative to the measured mean, which is deemed acceptable in engineering practice. The deflection values at various long-term time nodes indicate that the existing specifications generally overestimate the effect of creep when the concrete types are not taken into account. Although the predictions of the CEB90 model are closest to the model proposed in this paper, they are still 56.8%, 75.4% and 82.2% higher in the mid-span deflection at 3, 10 and 20 years after completion, respectively. Full article

This paper examines the applicability of the fracture forming limits (FFLs) derived from conventional monotonic upset compression tests for assessing the formability of non-monotonic strain loading paths. The work uses a simple test specimen subjected to various non-monotonic deformation histories, and combines experimental force measurements, digital image correlation, finite element analysis, and scanning electron microscopy (SEM) to characterize strain loading paths and crack opening mechanisms under varying testing parameters. Results demonstrate that non-monotonic strain loading paths can result in fracture strains that differ from those obtained through conventional monotonic bulk formability tests in the effective strain versus stress triaxiality space, depending on the considerations made in the transition between different loading stages. Consequently, reliance on monotonic test data may lead to inaccurate predictions of cracking in multi-stage industrial bulk forming processes. Full article

As a critical aerospace structural material, the fatigue crack propagation behavior and fatigue life of the nickel-based GH4169 superalloy are directly related to the service safety of engineering components. The crack closure effect is one of the key factors influencing the fatigue life of metallic materials. At present, the finite element method (FEM) is widely used to investigate fatigue crack propagation in metals. However, the commercial software ABAQUS 2021b employs the conventional Paris law for crack growth simulation, which neglects the influence of crack closure. In addition, ABAQUS cannot simultaneously perform fatigue life prediction and crack path prediction within a single numerical model. To overcome these limitations, the bi-prism-based single-lens (BSL) three-dimensional digital image correlation (3D DIC) technique was employed to experimentally investigate the crack closure behavior during fatigue crack propagation in GH4169 compact tension (CT) specimens. A new parameter, termed the crack opening ratio (COR), was introduced to quantitatively characterize the crack closure effect. Furthermore, a self-developed plugin was implemented on the ABAQUS platform through secondary development, enabling the numerical model to incorporate the influence of crack closure during fatigue crack propagation. The plugin automatically records the crack tip coordinates at each propagation step, calculates the stress intensity factors near the crack tip, and predicts the corresponding fatigue life, thereby integrating crack path prediction and fatigue life prediction within a unified framework. The results demonstrate that the COR effectively characterizes the crack closure effect in the numerical model, and the predicted fatigue life agrees with experimental results within an 11% deviation once the crack reaches a certain length. Full article