Digital Image Research Articles

Rapid examination of lung tissues by nonlinear microscopy.

Traditional histopathology is a time-intensive and labor-intensive process involving tissue formalin fixation, paraffin embedding, and microtoming into thin sections for H&E staining. Frozen section analysis is a modality used during surgery to quickly evaluate tissue, but it has limitations, such as the size and number of the specimens that can be analyzed as well as difficulties with fatty and bony tissues. Our objective was to investigate the performance of nonlinear microscopy, a fluorescence microscopy technique, for the rapid examination of resected lung tumors. In this proof-of-principle study, nonlinear microscopy imaging of resected lung tissue was performed on a total of 73 tissue specimens collected from 13 patients who underwent lobectomy, segmentectomy, or wedge resection for pulmonary nodules. Two pathologists reviewed the digital nonlinear microscopy images in comparison to the corresponding histopathologic H&E slides from a variety of pulmonary pathologies. This study demonstrated that nonlinear microscopy readily replicates traditional H&E staining for both lung tumors and nonneoplastic pulmonary structures. Nonlinear microscopy provides many advantages over frozen section analysis and is an optical imaging platform that has the potential to augment rapid pathologic evaluation of resected tissues in the age of digital pathology.

Investigation on the failure mechanism of hard rock cavern subjected to adjacent structural plane based on physical model experiments

Structural planes present significant safety challenges in the construction of deep hard rock caverns. However, the influence mechanism of a single dominant adjacent structural plane remains inadequately explored. This study conducted a series of physical model experiments with non-penetrating structural planes positioned adjacent to the cavern under uniaxial step compression, utilizing acoustic emission (AE) and digital image correlation (DIC) to monitor the failure process simultaneously. The results indicate that adjacent structural plane can mitigate stress-induced failure, reducing peak strength and elastic modulus by 10–42% and 13–31%, respectively. In the absence of a structural plane or a non-intersecting plane, stress-induced failure intensifies. Conversely, an intersecting plane contributes to greater crack stability. Precursor AE signals emerge earlier in the combination system. The intact cavern system shows an escalating tensile fracture ratio with loading, whereas the combination systems experience a diminishing tensile fracture ratio. Finally, particle flow code (PFC) simulation revealed that the presence of a single structural plane alters the cavern’s force chains, influencing stress concentration position. This research reveals that the structural plane has the potential to alter the cavern failure mechanism, providing insights into the complex interaction between structural planes and caverns in deep engineering.

The Effect of Resolution and Watermark Strength on Multi-level DWT Image Watermarking

With the widespread use of the Internet and the decrease in storage costs, many media have been transferred to digital media. This situation reduces the security and reliability of digital media. Media producers use watermarking methods for copyright protection. This study focuses on wavelet transform, which is one of the frequency conversion methods for watermarking. The wavelet transform for the watermarking process is usually applied on one of the four subbands obtained in a single level. In this study, the watermarking process is carried out in a total of 12 sub-bands, including the 1st, 2nd and 3rd levels. In addition, a performance evaluation metric for digital image watermarking is presented. The evaluation is applied using 10 different watermark strength factors on 46 different image resolutions. The Ultra High-definition Demoiréing Dataset is used for testing. The mathematical results obtained as a result of 22080 iterations are shown with tables and graphics, and the performance relations between the cover image resolution value and the sub-band selection are interpreted.

Nanoscale speckle patterning for combined high‐resolution strain and orientation mapping of environmentally sensitive materials

AbstractScanning electron microscopy‐based high‐resolution digital image correlation (HRDIC) is now an established technique, providing full‐field strain and displacement measurement at the microscale. Techniques for generating speckle patterns for sub‐micron strain mapping can often be either substrate dependent or rely on applying aggressive conditions which may alter the microstructure of interest or damage the substrate in highly sensitive materials. We detail a modification of a methodology successfully applied in the literature to allow its use with metallic materials that are particularly sensitive to the corrosive media, such as copper‐base alloys. Nanometre‐thick silver films, applied with physical vapour deposition, are remodelled using NaBr in non‐aqueous isopropanol, replacing the aqueous solution of NaCl in the original method, forming a uniform dispersion of silver islands highly suitable for digital image correlation (DIC) measurement. The entire procedure is performed at ambient temperature. We find that the DIC pattern is suitably electron transparent to allow electron backscatter diffraction (EBSD) measurements without pattern removal, producing diffraction patterns of sufficient quality for cross‐correlation based high‐angular resolution EBSD. This property facilitates simultaneous EBSD and DIC mapping experiments, providing deeper insights into the kinematics of plastic deformation in crystalline materials. Sub‐100 nm islands are achieved through control of the sputter coating parameters, resulting in DIC cross‐correlation subwindows of 140 nm with a 50% overlap. This resolution is sufficient to capture the fine detail of strain localisation phenomena during plastic deformation, demonstrated here with a case study in CuCrZr, a precipitation‐hardened heat sink material for application in nuclear fusion components. Here, we extract full‐field displacement data with DIC and corresponding orientation information using EBSD without the need for pattern removal.

Assessing measurement uncertainties on high-speed DCB testing of composites

This study investigates dynamic behavior in Double Cantilever Beam (DCB) tests across loading rates from 6 mm/min to 3 m/s. Comprehensive instrumentation has been used to investigate the sources of measurement errors (load, opening and crack length) or biases (asymmetry) and to quantify their effects on the fracture toughness determination using three variations of the Corrected Beam Theory. In particular, challenges in establishing zero load and displacement references were revealed through monitoring initial test phases. The resulting uncertainties in the fracture toughness have been estimated to be between 7 and 15%. Arms asymmetry during higher loading rates (1 m/s and 3 m/s) has been recorded using Digital Images Correlation. Using this data and a simple beam model, mode mixity (GII/GI from Williams approach) computed is in the order of 10%–20%.

Temperature Dependent Dynamic Response of Open-Cell Polyurethane Foams

Abstract Background Polyurethane foams have many uses ranging from comfort fitting seats and shoes to protective inserts in helmets and sports equipment. Current military helmet designs employ foam pads of varying densities and bulk material properties to help absorb energy from impacts ranging from quasi-static to ballistic level strain-rates. Objective This study aims to analyze the thermomechanical uniaxial compression behavior of a high density liner foam pad and a low density liner foam pad used in the Advanced Combat Helmet. These experiments were conducted under strain-rates of $$10^2$$ 10 2 s$$^{-1}$$ - 1 and under temperature conditions ranging from -20 to 40 °C. This temperature range was chosen to simulate desert and arctic conditions, with a strain-rate regime chosen to represent loads that would occur often throughout the life of the helmet, such as drops, bumps from riding in a vehicle, or heavy collisions from falling. Method Multiple experimental apparatuses were used in this study, including a Shimadzu TCE-N300 thermostatic chamber (used to create the varying temperature environments) and a custom-built drop-test system (used to induce intermediate strain-rates). Every experiment was paired with two accelerometers and a high speed camera used for Digital Image Correlation (DIC) to analyze sample deformation and resultant acceleration. The foam’s mechanical response and energy absorption properties were investigated from the measured stress-strain curves. Additionally, each foam composition was analyzed with X-ray computed micro-tomography (XCT) to investigate microstructure properties pre and post-mortem. Results Results show that temperature decreased the energy absorption of the low density composition by 48% ± 5% as temperature changed from -20 °C to 40 °C, while energy absorption increased by 53% ± 16% for the high density composition over the same temperature. Conclusion A comparison between the loading response and the material’s density characteristics revealed that the foam’s mechanical properties are heavily dependent on strain-rate applications, as well as environmental factors including temperature. Several important characteristics surrounding each foam composition’s deformation mechanics and damage tolerance as a result of temperature are discussed.

Investigation of the effects of volume fraction, aspect ratio and type of fibres on the mechanical properties of short fibre reinforced 3D printed composite materials

AbstractMechanical behaviour of 3D-printed composite parts is affected by the volume fraction, aspect ratio and type of fibre reinforcement. Although in the literature experimental approaches have been used to characterise the effects of the above factors on the mechanical properties of 3D printed parts, time and cost of the manufacturing process as well as the uncertainty associated with a large number of experimental techniques are the key issues. This study aims to address these challenges by developing a methodology based on a multi-scale Finite Element (FE) analysis of representative volume element (RVE) of 3D printed composite parts to predict the effective orthotropic properties. To account for the effects of fibre features, RVEs were modelled considering variables of volume fraction, aspect ratios and type of short fibres. To study the main and interaction effects of the above variables on the mechanical properties of 3D printed composite parts, a structured approach based on the Design of Experiments is used. The FE stress analysis of the RVE provides an understanding about the potential failure modes such as interfacial debonding between fibres and matrix, interlayer and intralayer delamination that may occur in load-bearing 3D printed composite parts. The FE computed mechanical properties are validated against experimental data through a series of mechanical testing of flexure, Iosipescu, and short beam shear which were conducted in conjunction with the Digital Image Correlation technique. As a result, certainty is obtained in using the proposed approach for a fast iterative design of 3D printed composite parts prior to industrial applications.

Image Compression Using Improved Method

Effective use of digital images requires certain techniques to lower the number of bits needed to represent them. The goal of compression is to reduce the size of an image while maintaining its information and originality. This research aims to achieve this target by developing a fuzzy logic and histogram-based image compression type detection approach. The main goal is to provide an approach that employs fuzzy logic and graphs for detecting the type of image compression. In order to decide the compression technique depending on the number of color levels in the image which was recovered with the use of histogram, the suggested technique combines a new combination of fuzzy logic as well as image histogram analysis. The experimental findings demonstrated the suggested technique's robustness and efficiency in detecting the best approach for each type of image compression. After 75 images with varying color densities were evaluated, the system's compression rate was approximately 95%. In addition to being a significant contribution to image processing, the study finds practical applications in the following areas: remote sensing through satellite; facsimile transmission of medical images in computer tomography magnetic resonance imaging; teleconferencing systems; military communication systems via radars; geological surveys; and communications systems built by computers.

Sensitive assessment of bilirubin using various color space signals derived from captured images of microfluidic paper-based analytical devices

Many neonates’ manifest hyperbilirubinemia and jaundice during the first week following birth because of bilirubin accumulation in the blood. Newborns with severe hyperbilirubinemia develop neurotoxicity. Therefore, sensitive, accurate, cost-effective, and timely determination of bilirubin levels is highly desired. Herein, we present three simple systems of bilirubin assessment based on spectrophotometric, and digital imaging tools. Image-capturing devices pose a formidable challenge to sophisticated spectrophotometers and field-monitoring devices because of their simplicity and sensitivity. The first and second systems of bilirubin assessment, in solution, relied on spectrophotometric and conventional color responses of digital images collected with conventional or android smartphone camera, with LODs of 0.060–0.082 and LOQs of 0.200–0.273 ppm bilirubin. The third system utilized a microfluidic paper-based analytical device (μ-PAD) that is patterned with a wax printer on Whatman grade-1 chromatographic papers, with linear calibration graphs of up to 2.70,s and LODs of 0.035–0.040 and LOQs of 0.117–0.133 μg bilirubin/μ-PAD.

Vein pattern visualization for CSAM investigation using deep learning

ABSTRACT Child sexual abuse material (CSAM) has become one of the fastest-growing criminal industries linked to other illegal activities, such as human trafficking, underage prostitution, and the sextortion of minors. Although common biometric traits such as fingerprint, face, and palmprint are widely used in traditional identification systems, they are ineffective in investigating CSAM cases, as perpetrators often conceal their faces, and only partial non-facial skin may be visible. Vein pattern visualization has been introduced as a new tool in forensic investigations to overcome the limitations of current identification methods. Our early research has shown promising results in uncovering vein patterns from normal digital images using computer vision and deep learning techniques. For this research, we use a dataset of forearms and palm images collected from 301 participants in New Zealand. Utilizing a deep learning framework, we develop a collection of mapping models to reveal unique vein patterns from regular digital images. The results demonstrate our method’s efficiency in visualizing vein patterns, indicating nearly 95% similarity in the contrast values between reference NIR and generated images and 79% in the vein length of the generated and target images.

Digital Image Correlation Analysis of Uniform Deformation and Necking in Solid‐State Welded Nanocrystalline Aluminum via High‐Pressure Torsion

Solid‐state welding of Al 1043 sheets was achieved via high‐pressure torsion (HPT) processing to produce bulk nanostructured Al disks. A homogeneous nanostructure without segregation was observed, with grain sizes of ∽430‐470 nm. Miniature tensile testing, coupled with the digital image correlation (DIC) technique, was employed to determine the room‐temperature tensile deformation behavior, particularly the non‐uniform behavior with necking, of the HPT‐bonded ultrafine‐grained (UFG) aluminum, comparing it with annealed coarse‐grained counterpart. The HPT‐bonded UFG Al exhibited a large fraction of post‐necking strain, which is supported by the estimated high strain rate sensitivity value of m = 0.085, suggesting the delay of local necking leading to tensile fracture. Detailed DIC analysis revealed prolonged diffuse necking, thus delaying local necking, in the HPT‐bonded UFG Al, while the annealed samples show high fractions of local necking during the non‐uniform deformation. Moreover, the DIC data illustrated that local necking predominantly occurred at a limited neck zone, maintaining a plateau strain distribution at the out‐of‐neck zone throughout necking deformation towards tensile failure for both annealed and UFG aluminum. The DIC method offers an alternative means to demonstrate the transition in necking behaviors of materials by estimating the plastic lateral contraction exponent.This article is protected by copyright. All rights reserved.

Experimental and numerical studies on a passively deformed coupled-pitching hydrofoil under the semi-activated mode

Flexibility is expected to positively affect the hydrodynamic and energy-harvesting performance of deformable hydrofoils, which have a simple structure and can be easily implemented in practical engineering applications. However, the characteristics of the fluid-structure interaction and power capturing are complicated. In this study, to reveal the fluid-structure interaction (FSI) mechanism and the effects of the passive deformation on the energy-harvesting performance, a flexible hydrofoil to conduct a coupled-pitching motion under the semi-activated mode was proposed and investigated experimentally and numerically. In the experimental study, a deformation-measuring technology based on a digital imaging algorithm was developed and employed for water channel tests. The effects of the hydrofoil profile and activated pitching amplitude on the deformation status, torque output, and energy-harvesting performance were studied experimentally. In the numerical study, a three-dimensional unsteady two-way FSI model was established and validated using experimental results. The influence mechanisms of the damping torque coefficient, activated pitching amplitude, and elasticity modulus on the passive deformation, its phase difference with the activated pitching angle, and the hydrodynamic and energy-harvesting performances were studied. Compared with the rigid hydrofoil, the energy-harvesting efficiency and power coefficient of the passively deformable hydrofoil could be increased by 4.8 % and 8.0 %, respectively, as the phase difference zone was close to 3π/4. In addition, positive and negative phase difference zones for performance enhancement were identified, which provides a future direction for optimizing flexible hydrofoils and control strategies.

The Fracture Evolution Mechanism of Tunnels with Different Cross-Sections under Biaxial Loading

Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital image correlation (DIC) system. Numerical simulations were performed on egg-shaped, U-shaped, and straight-walled arched tunnels based on the mesoscopic parameters of the elliptical tunnel and following the principle of an equal cross-sectional area. The meso-crack evolution and stress conditions of the four types of tunnels were compared. The results show that (1) fractures around an elliptical tunnel were mainly distributed at the end of the long axis and mainly induce slabbing failure, and the failure mode is similar to a V-shaped notch; (2) strain localization is an important characteristic of rock fracturing, which forebodes the initiation, propagation, and coalescence paths of macro-cracks; and (3) the peak loads of tunnels with egg-shaped, U-shaped, and straight-walled arched cross-sections are 98.76%, 97.56%, and 90.57% that of an elliptical cross-section. The elliptical cross-section shows the optimal bearing capacity.

Forensic anthropological research in Indonesia: developing a sex estimation standard for the contemporary population

ABSTRACT Currently, there are a lack of forensic anthropological sex estimation standards for an Indonesian population. Morphoscopic assessments were considered for its ease of use and application to fragmentary remains. For the skull, the cranial nonmetric traits in Walker (2008) are the most frequently used standard. Digital imaging modalities are considered an appropriate proxy to physical skeletal material. This present study assesses the accuracy of Walker (2008) and Asian-derived models in Tallman (2019) on a contemporary Indonesian population. Five univariate and nine multivariate predictive models were derived. This study provides forensic practitioners with an appropriate skeletal sex estimation standard for use in Indonesia, strengthening their capabilities.

Image Forgery Detection Using Machine Learning

Digital Image Forgery can be done by deceiving the digital image to mask some meaningful or important data of the image. It is usually difficult to spot out the manipulated region of the original image. To sustain the uprightness and legitimacy of the image, the detection of forgery in the image is mandating. Acclimation of the modern way of life and advancement in photography gadgetry has made exploitation of digital image easy with the help of image editing software. Therefore, it is crucial to detect such image forgery operations in the images. The image forgery detection can be done based on object removal, object addition, unusual size modifications in the image. Images are one of the powerful media for communication. In this project we have used algorithms such as Copy move, Canny Edge Defection, Structure Similarity index, Hierarchical Agglomerate Clustering and Neural Network algorithms with improved accuracy rate.

FACE DETECTION SYSTEM USING CONVOLUTIONAL NEURAL NETWORKS: A REVIEW

Implementing a facial recognition system can help in identifying or verifying the identity of a person from a digital image. Accurate attendance records are critical to classroom assessment. However, manual attendance tracking can lead to errors, missed students, or duplicate records. The facial recognition attendance system includes facial recognition technology that recognizes and verifies an employee's facial features and automatically records attendance. The facial liveliness detection part is based on CNN, which creates a 3D model of the detected face to distinguish between real and fake images. The attendance system is written in Python and the user interface is designed using the WebView library. The main goal of facial recognition is to identify individuals, either individually or collectively. The number of positive faces may vary depending on the technology used for face recognition. Keywords: Face Recognition Attendance System, CNN Algorithm.

Spatial Distribution of Macrophage and Lymphocyte Subtypes within Tumor Microenvironment to Predict Recurrence of Non-Muscle-Invasive Papillary Urothelial Carcinoma after BCG Immunotherapy.

Non-muscle-invasive papillary urothelial carcinoma (NMIPUC) of the urinary bladder is the most common type of bladder cancer. Intravesical Bacille Calmette-Guerin (BCG) immunotherapy is applied in patients with a high risk of recurrence and progression of NMIPUC to muscle-invasive disease. However, the tumor relapses in about 30% of patients despite the treatment, raising the need for better risk stratification. We explored the potential of spatial distributions of immune cell subtypes (CD20, CD11c, CD163, ICOS, and CD8) within the tumor microenvironment to predict NMIPUC recurrence following BCG immunotherapy. Based on analyses of digital whole-slide images, we assessed the densities of the immune cells in the epithelial-stromal interface zone compartments and their distribution, represented by an epithelial-stromal interface density ratio (IDR). While the densities of any cell type did not predict recurrence, a higher IDR of CD11c (HR: 0.0012, p-value = 0.0002), CD8 (HR: 0.0379, p-value = 0.005), and ICOS (HR: 0.0768, p-value = 0.0388) was associated with longer recurrence-free survival (RFS) based on the univariate Cox regression. The history of positive repeated TUR (re-TUR) (HR: 4.93, p-value = 0.0001) and T1 tumor stage (HR: 2.04, p-value = 0.0159) were associated with shorter RFS, while G3 tumor grade according to the 1973 WHO classification showed borderline significance (HR: 1.83, p-value = 0.0522). In a multivariate analysis, the two models with a concordance index exceeding 0.7 included the CD11c IDR in combination with either a history of positive re-TUR or tumor stage. We conclude that the CD11c IDR is the most informative predictor of NMIPUC recurrence after BCG immunotherapy. Our findings highlight the importance of assessment of the spatial distribution of immune cells in the tumor microenvironment.

Sensor synchronized DIC: A robust approach to linear and nonlinear modal analysis using low frame rate cameras

Digital image correlation (DIC) is a non-contacting, optical method for measuring full-field displacements. Recently, there has been interest in DIC as a tool for experimental modal analysis. Currently DIC necessitates the use of high-speed cameras that satisfy the bandwidth requirements for the system under investigation. High-speed cameras, however, tend to be expensive, bulky, and low-resolution, thus limiting their application. In contrast, low-speed cameras tend to be cheaper, smaller, and higher-resolution. In this work an alternative approach that utilizes low-speed cameras is developed. The approach functions by synchronizing image capture against a high bandwidth reference sensor. This enables images to be precisely captured at prescribed moments in a waveform. A basic algorithm is developed for the synchronization, including an uncertainty analysis to estimate phase errors arising from the approach. The method is then demonstrated by using low-speed cameras to estimate the full-field amplitude response of a thin, cantilevered plate. This is achieved by alternating image capture between extremums during a swept-sine test. The excitation level is then increased to elicit a highly nonlinear response from the plate. Measurements are repeated to demonstrate that the approach works even when the system exhibits large harmonic distortions.

Machine learning-based wood anatomy identification: towards anatomical feature recognition

Summary Computer vision-based wood identification has been successfully applied to recognize tree species using digital images of wood sections or surfaces. However, this image-to-species approach can only recognize a limited number of species due to two main reasons: 1) the lack of a good reference database requiring high-quality standardized images from multiple individuals of hundreds or even thousands of traded timber species, and 2) species not included in the reference database cannot be identified without expert knowledge. Another bottleneck is that the feature extraction process used by these species recognition approaches is a black box, thereby creating a discrepancy between machine learning features and wood anatomical features. This discrepancy prevents wood anatomists from understanding how these machine-learning algorithms work. Here, we survey currently existing methods used in feature extraction, classification, and deep learning methods applied in wood identification along with their pitfalls and opportunities. As an example of how the field could move forward, we launch the idea of building an image-to-features-to-species identification approach based on microscopic wood images as well as text files comprising wood anatomical descriptions. If we can manage machine learning-based algorithms to recognize the main wood anatomical traits that experts use to identify species in a (semi-)automated way, this would boost wood identification in two ways: (1) extensive reference databases for each species would become less crucial as the databases are ordered at the trait level, (2) timber identification would become more feasible for species that have not yet been included in the reference database as long as wood anatomical descriptions are available.

New Technologies and Specialist Competencies in the Complex Study of Digital Images of a Person’s Appearance

New Technologies and Specialist Competencies in the Complex Study of Digital Images of a Person’s Appearance