Digital Image Research Articles

Design of mean filter using field programmable gate arrays for digital images

In this paper, we design and analysis of mean filter using field programmable gate arrays (FPGAs) for digital images, FPGAs are integrated circuits consisting of interconnections that connect programmable internal hardware blocks allows users to customize operations for a specific application. FPGA is an ideal choice for real-time image processing, these FPGA devices are controlled in Verilog or VHDL languages, allowing to design at different levels and adapt to design changes or even support new applications throughout the life of the component. Digital image filtering is the most important task in image processing and with the help of computers, image recognition involves identifying and classifying objects in an image. This paper design of mean filter for digital image processing, implementation and analysis of image processing algorithms on FPGAs. The results obtained on the FPGA are compared and analyzed with the results by MATLAB software.

An artificial intelligence approach to smart exam supervision using YOLOv5 and siamese network

<p>Artificial intelligence has introduced revolutionary and innovative solutions to many complex problems by automating processes or tasks that used to require human power. The limited capabilities of human efforts in real-time monitoring have led to artificial intelligence becoming increasingly popular. Artificial intelligence helps develop the monitoring process by analysing data and extracting accurate results. Artificial intelligence is also capable of providing surveillance cameras with a digital brain that analyses images and live video clips without human intervention. Deep learning models can be applied to digital images to identify and classify objects accurately. Object detection algorithms are based on deep learning algorithms in artificial intelligence. Using the deep learning algorithm, object detection is achieved with high accuracy. In this paper, a combined model of the YOLOv5 model and network Siames technology is proposed, in which the YOLOv5 algorithm detects cheating tools in classrooms, such as a cell phone or a book, in such away that the algorithm detects the student as an object and cannot recognize his face. Using the Siames network, we compare the student’s face against the data base of students in order to identify the student with cheating tools.</p>

Effect of Lateral Pressure on the Stability of Inclined Layered Rock Tunnel: A 3D-printed Model Investigation by Cement-based Materials

The inclined layered rock tunnel engineering in the alpine canyon area subject to tectonic stress will be influenced by high lateral stress. Currently, there are scarce reports on the impact of the lateral pressure coefficient on the stability of inclined layered rock tunnels. Hence, the mechanical response of the inclined layered tunnel model was investigated based on the 3D-printed model test, supplemented by acoustic emission (AE) and digital image correlation (DIC) monitoring methods under three cases of lateral pressure coefficients of 1.2, 1.5 and 1.8. The results reveal that for the tunnel model with a 60° bedding inclination, the bearing capacity is negatively correlated with the lateral pressure coefficient. The normal deformation of the bedding of the tunnel model is prominent, exhibiting significant asymmetric deformation characteristics. When the lateral pressure coefficient k increases from 1.2 to 1.5, the failure of the tunnel model changes from shear-slip failure along the layer to bedding cracking and buckling failure of the sidewall. The test results have enlightenment significance for the stability evaluation of inclined layered surrounding rock tunnels in the alpine canyon area.

Presence of abnormal otoliths in hallucinogenic fish and their comparison with normal otoliths using light and scanning electron digital imaging.

The otolith organs located in the inner ear of the fish are responsible for vital activities such as balance and hearing. Abnormalities in these organs can adversely affect the vital activities of the fish species. The main purpose of the study is to analyze the abnormalities in the otoliths of Sarpa salpa, known as the hallucinogenic fish. For that, 372 individuals of S. salpa are collected from the North Aegean Sea. As a result of the abnormality analyses in S. salpa otoliths, anomalies were detected such as various prominence structures on the surface of the otolith caused by accumulation and a more transparent appearance due to the different crystal structures in some parts of the otolith. These abnormalities were found in the left and/or right otoliths of male and female individuals in different total lengths. The percentage of individuals with abnormal otoliths of S. salpa is calculated as 52.42%. It was determined that there are statistical differences between the left and right otolith measurements of male and female individuals with abnormal and normal otoliths(p < 0.05). There is no relationship between the percentage of individuals showing abnormality and total length and sex. The current study presents for the first time abnormal otolith information on left and right otoliths in male and female S. salpa. It is thought that abnormalities in hallucinogenic fish otoliths could be related to genetic predisposition as well as stress due to nutritional preference, pollutants, and environmental factors. RESEARCH HIGHLIGHTS: The presence of abnormalities in the otoliths of Sarpa salpa, a hallucinogenic fish, was revealed for the first time. Abnormalities in the otoliths of S. salpa were identified, such as the presence of various prominence structures on the otolith's surface, loss of parts as well as a more transparent appearance in the outlines or surface of the otolith. Normal and abnormal otoliths of female and male hallucinogenic fish from different size groups were examined using light and scanning electron microscopy. Abnormality detected in the otoliths of hallucinogenic fish is not related to the gender and size of the fish.

MICRO-MESO CHARACTERIZATION OF PREFABRICATED CONCRETE-CLT ADHESIVE JOINTS

This study evaluates the use of five commercially available epoxy adhesives (EAs), from low to high cost, as a connection alternative of timber-concrete composites (TCCs) using cross-laminated timber (CLT) and medium-strength precast concrete (25MPa). Five alternative EAs were initially evaluated via pull-off tests to determine the adhesive strength of the interface CLT/concrete, with average results varying from 0.6MPa to 3.6MPa. Subsequently, optical and scanning electron microscopy analyses were implemented to assess the microstructure of post-tested TCC specimens, finding that usually the CLT/concrete interface was not fully glued by the EAs and that there was a positive correlation between the penetration of each EA with the corresponding tension strength of the TCCs. Then, the three EAs with the largest adhesive strengths were further tested by small double-shear (SDS) tests evaluating their shear strength and deformation, as well as damage evolution and failure modes, which were obtained using digital image correlation. The SDS test average results ranged from 2.4MPa to 8.8MPa, and the EA with the best behavior was not the one with the highest tensile strength, but rather with the highest EA penetration into concrete, demonstrating that this property highly positively impacted the shear strength of TCCs. Finally, cost/benefit analyses were obtained, and interestingly, the EA with the best adhesive/shear performance was not the most expensive alternative, opening the discussion that, even though mostly expensive EAs have been used in TCCs, the option of technically valid and low-cost EA is feasible.

Improved fracture toughness evaluation for fiber-reinforced asphalt concrete through double-parameter theory

Fracture toughness serves as a key parameter in the design and durability assessment of asphalt concrete. Quantifying the fracture toughness for fiber-reinforced asphalt concrete (FRAC), remains challenging due to the incorporation of fibers. This study proposes an improved method for evaluating the fracture toughness of FRAC, based on the double-parameter theory derived from the theoretical concepts of stress intensity factor K and energy release rate (double-K and double-G fracture models). Using Digital Image Correlation (DIC) technology, crack propagation during three-point bending beam tests on FRAC beams was measured, refining the calculation of critical crack length ac in the double-K fracture parameters. Additionally, a method is introduced to calculate the improved solution of double-G fracture parameters by monitoring crack propagation in real-time to determine the effective crack length a, and simultaneously computing the energy absorbed per unit crack extension, thereby constructing the J-R curve during stable crack growth phases. The fracture toughness of FRAC is evaluated by the improved method obtained double-G fracture parameters were used in Virtual Crack Closure Technique (VCCT) simulations to achieve virtual modeling of FRAC. The results demonstrate that the improved method provides accurate fracture performance indicators for FRAC. Moreover, the study establishes modified calculation formulas for (GICu) and (KICu) at unstable fracture toughness for FRAC at different temperatures, considering various fiber types and contents, thereby enhancing computational efficiency for practical applications. This research contributes to more accurate and effective methods for testing and evaluating the fracture performance of FRAC

Deep ensemble architectures with heterogeneous approach for an efficient content-based image retrieval

&lt;span lang="EN-US"&gt;In the field of digital image processing, content-based image retrieval (CBIR) has become essential for searching images based on visual content characteristics like color, shape, and texture, rather than relying on text-based annotations. To address the increasing demands for efficiency and precision in CBIR systems, we introduce the HybridEnsembleNet methodology. HybridEnsembleNet combines deep learning algorithms with an asymmetric retrieval framework to optimize feature extraction and comparison in extensive image databases. This novel approach, specifically custom-made for CBIR, employs a lightweight query structure skilled at handling large-scale data under resource-constrained environments. The experiments were performed on the ROxford and RParis datasets. The deep learning component of HybridEnsembleNet significantly refines the accuracy of image matching and retrieval. RParis The ROxford dataset, specifically in the medium and hard difficulty benchmarks, demonstrates an enhancement of 5.53% and 10.44%, respectively. Similarly, the RParis dataset, under medium and hard benchmarks, exhibits improvements of 3.01% and 5.83%, showcasing superior performance compared to existing models. By overcoming the traditional limitations of CBIR systems in mean average precision (mAP) metrics, HybridEnsembleNet provides a scalable, efficient, and more accurate solution for retrieving relevant images from vast digital libraries.&lt;/span&gt;

Use of artificial intelligence in banknote reconstruction

Banknotes may be damaged during various events, such as floods, fires, insect infestations, and mechanical or manual shredding. Disaster victims might need to perform banknote reconstruction when applying for currency exchange, or investigative agencies might need to conduct such reconstruction during evidence collection. When the number of banknote fragments is small, they can be manually assembled; however, when this number is large, manual assembly becomes increasingly difficult and time-consuming. Therefore, an automated and effective method is required for banknote reconstruction. The process of banknote reconstruction can be considered similar to solving a large-scale jigsaw puzzle. This study employed an artificial intelligence (AI) system to reconstruct damaged banknotes. A robotic arm was used to replace manual separation and automated digital image processing techniques, and AI image registration technology, deep learning, and logical operations were utilized. A deep convolutional neural network was used to estimate the relative homography between images, and fragmented banknotes were mapped to a reference banknote for image transformation, thereby reconstructing the damaged banknotes. Additionally, a repetitive matching method was established to optimize the matching results to achieve the best possible mapping and enhance validation efficiency.

Investigation of scale effects of rock bridges based on Multi-Physical field monitoring

The presence of rock bridges is crucial for ensuring the stability of rock slopes. However, evaluating the mechanical properties of rock bridges solely based on the joint persistence coefficient (K) raises doubts due to potential variations in the scales of rock bridges within a rock mass with a constant K value. In this study, direct shear tests with different scales were carried out on sandstone specimens. Acoustic Emission (AE) and Digital Image Correlation (DIC) techniques were utilized to monitor the damage procession of the specimens. The evolution process of the specimen was divided into stages and three threshold points were determined based on AE parameters. As the scale decreased, the Joint Roughness Coefficient (JRC) increased, the tensile failure increased, and the shear failure decreased. As the normal stress increased, the JRC with the same scale decreased, the tensile failure decreased, and the shear failure increased. The change of fracture mechanism was the primary reason for the strength deterioration with decreasing scales. The decrease of the scale was not conducive to the failure prediction. By improving the rock bridge failure potential (RBP) index, the proposed RBPn index could appropriately characterize scale effects under different normal stresses.

Dynamic splitting tensile properties of high-strength ultrahigh-toughness cementitious composites (HS-UHTCCs)

In this study, the splitting tests were conducted to examine the effect of strain rate on the splitting tensile performance of high-strength ultrahigh-toughness cementitious composites (HS-UHTCCs). Hydraulic machine and split Hopkinson pressure bar (SHPB) were used to investigate the tensile properties of HS-UHTCCs. The strain rates ranged from 10-6 to 10-3 s−1 for hydraulic machine experiments and from 5 to 15 s−1 for SHPB tests, respectively. The splitting tensile strength, tensile stress-strain curves, dynamic increase factor (DIF) and energy absorption ability of HS-UHTCCs were analyzed. The new DIF models proposed for HS-UHTCCs fit well with the experimental data. In addition, the failure modes of specimens and fibers were investigated. The splitting tensile strain was obtained from digital image correlation (DIC) tests. The results indicate that the strain rate has a significant effect on the splitting tensile strength and energy absorption ability of HS-UHTCCs. On the contrary, the average splitting tensile strain showed a decreasing trend with the increase of strain rate. Besides, the DIF model of HS-UHTCCs was proposed with experimental data. The failure modes of specimens changed at high strain rates, transitioning from remaining intact to completely splitting into half. Two failure patterns of polyethylene (PE) fibers included pull-out failure and rupture were observed, while steel fibers experienced pull-out failure.

Micro-mechanical performance study of the interfacial transition zone in ultra-high performance concrete containing coarse aggregates based on digital image correlation method

To measure the mechanical properties of the interfacial transition zone (ITZ) in ultra-high performance concrete with coarse aggregates (UHPC-CA) under direct load, a mesoscopic experimental analysis is performed using a combination of an electron microscope (EM) camera and digital image correlation (DIC) technology in this study. With such a methodology, the stress-strain curve of the ITZ under compression is measured directly. Furthermore, the distribution of the nominal compressive elastic modulus (E⁎) and Poisson's ratio (v) of the ITZ is obtained. Finally, the effects of granulated blast-furnace slag (GGBS) contents (0%, 30%, 40%, and 50%) on ITZ’s properties are investigated, and their relevance to microstructure is further explored by scanning electron microscope (SEM). The results indicate that the E⁎ in the ITZ follows a 'U'-shaped distribution. In comparison to the reinforced matrix, a compaction process in ITZ is observed obviously, resulting in a smaller v in this region. Besides, as the GGBS content increases, the mesoscopic mechanical properties of the ITZ gradually decline.

Debonding behavior of non-welded wrapped composite X-joints subjected to monotonic tensile load – numerical study and validation

The dominant failure mode in the non-welded wrapped composite joints made with GFRP composite material wrapped around steel circular hollow sections (CHS) is characterized as interface debonding. However, in the ultimate load joint experiments, debonding process was merely inferred from the surface strain distribution obtained by the digital image correlation (DIC). A thorough understanding and explicit illustration of debonding mechanism in wrapped composite X-joints is needed with help of finite element modeling (FEM), in order to provide prediction models for design of wrapped composite joints in engineering structures. In this paper, two FE models were developed to simulate the debonding behavior of small-scale and medium-scale wrapped composite 45° X-joints in monotonic tensile tests previously conducted by the authors. A new strategy of modeling complex composite geometry using 4-node tetrahedral elements (C3D4) without defining composite lay-up was proposed. The cohesive zone modeling (CZM) approach was utilized to simulate the debonding behavior of composite-steel interface with introduction of a new four-linear traction-separation law. The generated FE models were validated by good agreement between numerical and experimental results in terms of load-displacement response and surface strain distribution throughout the failure process at two joint scales. The validated models gained good insight into the joint debonding mechanism and determined the surface strain threshold for quantifying the debonding length. Development and validation of the FE models with unique set of parameters aligned well with the experiment results at two different scales is an important step for prediction and design of wrapped composite joints.

Exploring mechanical properties and cracking behavior of AC-13 and OGFC-16 aggregate-segregated asphalt mixtures

Aggregate segregation compromises the homogeneity of asphalt pavement, which diminishes the road performance of the asphalt mixture. The segregation behavior and damage mechanism of asphalt mixture are complex. To investigate the mechanical properties and cracking behavior of asphalt mixtures with varying degrees of aggregate segregation, the dense-graded asphalt mixture with the nominal maximum size of 13.2mm (AC-13) and Open Graded Friction Course with the nominal maximum size of 16.0mm (OGFC-16) with varying degrees of segregation were designed. Indirect tensile test and the digital image correlation (DIC) technology was employed to analyze the strain distribution and strain evolution at the crack initiation point within the asphalt mixtures. The parameters were also proposed to evaluate the resistance to cracking for the segregated asphalt mixtures at a mesoscopic scale. The results show that increased segregation of coarse aggregates in AC-13 mixtures leads to decreased indirect tensile strength, lower maximum tensile strain along the horizontal direction (E11), and reduced failure displacement. Conversely, segregation of fine aggregates in OGFC-16 mixtures results in increased tensile strength, maximum strain, and failure displacement. Higher amount of coarse aggregates in the asphalt mixture contributes to a more intricate strain distribution and a greater number of strain peaks. Dense-graded mixtures show larger strain concentration zones prior to cracking, while smaller stress concentration zones are observed in open-graded mixtures. The horizontal strain-time curve displays distinct stages of stable growth, rapid growth, and rapid decline. Aggregate segregation results in more intricate crack patterns with larger inclination angles, influenced by the random distribution and shapes of coarse aggregates. Novel indexes such as strain uniformity (P1,2) and strain density during crack development (DW) effectively evaluate mesoscopic cracking resistance of asphalt mixtures. The results offer valuable insights into cracking behavior and improve evaluation methods for the mechanical performance of aggregate-segregated asphalt mixtures.

Experimental and numerical investigation on the failure behaviors of laminates with various shaped cutouts under tensile loading

Composite structures in aircraft often contain many cutouts, and failure of these structures is prone to occur near the edge of cutouts. Therefore, the failure behaviors of laminates with various shaped cutouts should be carefully investigated. To this end, experiments and numerical simulations are employed to investigate this issue. The tensile tests of composite laminates with circular, elliptical, square, and rectangular cutouts were carried out. Digital image correlation was utilized to capture the strain fields around the cutout. Combining the strain failure criterion and the modified exponential damage variables a three-dimensional progressive damage model was established, which can accurately predict the peak loads of composite laminates with diverse cutouts. All errors between the experimental and numerical results are less than 10 %. The experimental and numerical results indicate that the shape of the cutout has a great influence on the peak loads. As the ratio of major axis to minor axis (a/b) is increased from 1 to 5, peak loads obviously increase for the laminates with elliptical cutouts. Experimental results show that the average peak load of the laminates with elliptical cutout (a/b = 4) is 20.0 % higher than that of the laminates with circular cutout (a/b = 1). The dispersed distribution of high strains near the edge of the cutout results in an improvement of bearing capacity. As the ratio of length to width (l/w) in rectangular cutouts is increased from 0.5 to 3, peak loads are also improved obviously, because experimental results show that the average peak load of the laminates with rectangular cutout (l/w = 0.5) is 12.3 % lower than that of the laminates with square cutout (l/w = 1). Therefore, to improve the peak loads, it is very necessary to select the proper ratios of a/b and l/w. The above conclusions can serve as a reference for the design of composite structures.

Shock Response of Sandwich Panels with Additively Manufactured Polymer Gyroid Lattice Cores

This work evaluates the shock response of sandwich structures with gyroid lattice cores made from Polylactic Acid (PLA), Acrylonitrile Butadiene Styrene (ABS), and Thermoplastic Polyurethane (TPU) using shock tube experiments coupled with high-speed photography and digital image correlation (DIC). The study found that gyroid lattice structures exhibit high energy absorption capacity and good structural integrity under shock loading, making them suitable for high strength-to-weight ratio and energy absorption applications in aerospace and defense industries. The sandwich panel with a TPU-core structure exhibited the highest deformation under shock loading, with a maximum deflection of approximately 6mm, followed by ABS at 0.9mm and PLA at 0.82mm. Under shock loading, the sandwich panel with TPU gyroid core exhibited the highest specific deformation energy (0.146J/g), which is consistent with its flexibility, though it remained in the same general order as ABS (0.104J/g) and PLA (0.070J/g). Interestingly, the specific total energy of the TPU gyroid core sandwich, while the lowest at 39.310J/g, was still relatively close to ABS (54.098J/g) and PLA (52.620J/g), despite the substantial difference in inherent stiffness of TPU compared to ABS and PLA. This suggests that while TPU's stiffness is much lower compared to PLA and ABS, its total energy absorption capability in gyroid form is not as drastically reduced, indicating the importance of geometry and mass distribution within the gyroid structure. Overall, the results of this study highlight the importance of careful design and optimization of these structures to utilize their unique properties fully.

DEM simulation of the compression of crushable sand: does the initial particle shape matter?

Advances in DEM modeling, combined with high-resolution X-ray tomography, opened the way for computer models based on virtual replicas of the particles to preserve nearly all facets of their geometry. This leads to simulation advantages, but also high computational costs. Here we tackle a question stemming from this trend: how accurate should particle models be to ensure accuracy? We address this question for the case of the compression of crushable sand. LS-DEM was used to generate three models of Ottawa sand (exact replicas, ellipsoids, and spheres) from digital images of its grains. Compression-induced crushing was simulated for all sets by tracking evolving size and shape distribution. The results confirm that exact replicas provide the closest match of the measurements. However, intermediate degrees of rendering (e.g., ellipsoids preserving volume and aspect ratio of the real grains) led to satisfactory results only marginally different from those of exact replicas. These findings provide an example of the protocols that may be followed to identify the optimal degree of particle approximation which should be regarded as mandatory to achieve a conscious, sustainable use of computational resources.

Damage model of NC-UHPC interface zone in UHPC wet joint based on DIC

The bond interface of the ultra-high performance concrete (UHPC) wet joint composed of normal concrete (NC) and UHPC is a weak part, which can easily damage the interface zone and affects the structure's safety. However, the damage model of the NC-UHPC interface zone in UHPC wet joint has not been carried out yet. In this study, firstly, the effects of different interfacial moisture content and interfacial roughness on the interfacial bond strengths were investigated by splitting tensile tests, NC-UHPC specimens with different interfacial bond strength were obtained, and digital image correlation (DIC) technique was used to obtain the strain evolution regulation of the NC-UHPC interface zone; Secondly, the extended interface zone damage factor Df was used to investigate the damage differences of NC-UHPC interface zone with different bond strengths; Finally, the damage model of NC-UHPC interface zone with different interfacial bond strengths was established. This research will be of great significance in improving the theoretical system of UHPC wet joint structure design.

StegaCrypt Integrating Hybrid Cryptography and Image Steganography

This paper discusses the combination of cryptography and steganography for digital data security. Cryptography and steganography are two of the most significant techniques in information security, to be used differently: data is secured against unauthorized use and ensured integrity by way of transforming it into some unreadable format, whilst steganography hides a file inside another file. The project aim is to synthesize the techniques for a robust system to protect secure communication and data. We use RSA cryptography for the encryption, which is the asymmetric algorithm of high-level security, and image-based steganography to place the encrypted data within a digital image. The processes of cryptography will ensure decrypting the data only in the hands of authorized recipient parties, and steganography provides additional protection on the data invisibility front. This project shows that this integration of two technologies will safeguard sensitive information from all types of threats. In view of various methods to combine cryptography and steganography, this project puts forward the significance of incorporating multi-layer security to combat different types of cyber-attacks. The implementation also includes an elaborated coding using algorithms and development of a GUI to facilitate user interaction with the system. This further ensures that it is not only technically sound but also user-friendly. The last system is to send confidential data toward the broader field of secure communications and information protection, efficiently, securely, and in a user-friendly way

APPLICATION OF THE ALGORITHM OF PARAMETRIC AND NON-PARAMETRIC CONFIDENCE INTERVALS IN PRE-PROCESSING IMAGE DATA

Digital image processing and enhancement is one of the most important and frequently used issues in many fields of image processing. When handling images or sending them over a particular channel, they are subject to certain noise and require filtering methods. In this paper, the parametric confidence interval algorithm was compared to the nonparametric confidence interval algorithm for processing the noisy images. The results showed that a nonparametric confidence interval algorithm is better at defining the external parameters of an image in terms of noise elimination and enhancement landmarks.

METHODOLOGY FOR THE APPLICATION OF THE DIGITAL IMAGE CORRELATION (DIC) FOR INVESTIGATING RC BEAMS

The article discusses the improvement of the digital image correlation (DIC) method for analyzing deformations in RC beams, specifically focusing on the importance of zero-strain verification. This step is critical for ensuring high measurement accuracy, as it helps identify and minimize systematic and random errors. Before starting the research, system calibration is conducted, which includes the assessment of background noise and stability that influence the results. The study shows that proper sample preparation, pattern creation, and control of external factors allow for obtaining reliable data. The application of DIC enables remote monitoring of cracks and evaluation of the stress-strain state of structures. It has been established that this method is useful not only for scientific experiments but also in practical engineering, contributing to the increased reliability of structures.