Image Processing Program Research Articles

Image processing methods based on physical models

In order to achieve better image processing results, the author proposes research on image processing methods based on physical models. The author first developed a simple and user-friendly GUIDE interactive interface based on Matlab software and image processing technology. Calculate and process the interference fringe patterns captured in static and dynamic experimental measurements in optical experiments separately to achieve experimental measurement objectives. Secondly, the image processing program was analyzed to highlight important information using methods such as Gaussian blur and binarization, and algorithms were used to construct surface 3D images or detect stripe motion features, establish 3D models, and accurately calculate corresponding experimental results. The final experimental results indicate that the phase transition value of piezoelectric devices increases linearly with the increase of voltage, which is consistent with the working characteristics of piezoelectric devices in the linear region. This program can analyze the image sets of horizontal, vertical, and oblique stripes, and calculate the piezoelectric moduli of piezoelectric devices to be 3.355 nm/V, 3.120 nm/V, and 3.557 nm/V, respectively, with relative errors of E1 = 4.9 %, E2 = 2.9 %, and E3 = 12 %. This method is suitable for various complex experimental measurement scenarios and provides an intuitive method for innovative design of optical interference experimental measurement teaching.

Analysis of Differences in Cystic Ovarian Neoplasm Volume on Abdomen-Pelvis MRI with Manual Measurement Technique (Linear Measurement) and Active Contour Laplacian of Gaussian (LoG) Technique

MRI image evaluation of cystic ovarian neoplasms was done manually and is generally carried out by Radiologists using a manual technique called linear measurement. This technique has some weaknesses, including being considered a rough calculation estimate because measurements are made on only one largest slice and are vulnerable to subjectivity factors. This research applied a digital image processing program based on Matlab using a segmentation process and active contour Laplacian of Gaussian (LoG) in the measurement and calculation of the volume of cystic ovarian neoplasms. Analyze the differences in measurement results and find out which technique is better in the calculation of cystic ovarian neoplasm volume between techniques of linear measurement and techniques of active contour Laplacian of Gaussian (LoG). The research was done with 32 images of abdominal-pelvic MRI images with clinical cystic ovarian neoplasms, and measurements and calculations of the volume of cystic ovarian neoplasms were carried out using the technique linear measurement and active contour Laplacian of Gaussian (LoG). Measurement and calculation are done by Radiologists as an observer with data analysis using statistical processing. Analysis of MRI images of abdominal-pelvic MRI images with clinical cystic ovarian neoplasms using linear measurement and active contour Laplacian of Gaussian (LoG) techniques showed a difference with a p-value of 0.004 (p<0.05). The results of measurements using the active contour laplacian of the Gaussian technique are better than the linear measurement, as indicated by the higher mean rank of the active contour laplacian of Gaussian, which was 17.50 (higher than the linear measurement value of 13.50).

Automatic Measurement in Metallography

Quantitative analysis of the structure of metals and alloys is an important part of modern metal science. To obtain quantitative data and build dependencies, metallographic image processing programs are used, oriented both for scientific research and for use in industry. Programs capable of automatically performing metallographic analysis are of great interest to consumers. When advertising such programs, it is often claimed that they allow quantitative analysis of the structure with virtually no time. The purpose of this work was to determine the time spent on quantitative metallographic analysis in some image processing programs presented on the Belarusian market. Connected and unconnected metallographic objects were considered. It is shown that automatic quantitative analysis is possible for unconnected objects (powders, cast iron graphite). The time required is within a minute. For connected objects (structures of metals and alloys after metallographic etching), the time required to detect objects and obtain digital data is 10–40 min or more, depending on the complexity of the object, which is unacceptable for factory laboratories that analyze a large number of samples per shift. Therefore, it is recommended that potential users of metallographic image processing software always require a substantive demonstration of the automatic measurement capabilities of the proposed software.

Development of Real-Time Monitoring System Based on IoT Technology for Curing Compound Application Process during Cement Concrete Pavement Construction.

Among the construction processes of Portland cement concrete pavement (PCCP), the curing compound spraying process is one of the most important processes. If the curing compound spraying amount does not meet the standard or if the curing compound is not applied evenly, distresses occur at the early age of construction, ultimately causing deterioration in concrete pavement performance. The purpose of this study is to develop a real-time monitoring system for a curing compound spraying process based on the Internet of Things (IoT) and sensing technologies to improve the construction quality of concrete pavement. To achieve the goal of this research, we conducted various laboratory and field experiments. The curing compound spraying amount and sprayed status were measured and analyzed using flowmeters, image acquisition sensors, and an image processing program, and the data were provided to workers in real time and simultaneously transmitted to the IoT cloud to form a database. From this study, it is confirmed that the IoT-technology-based curing compound spraying amount and sprayed status monitoring systems can be successfully established to manage construction quality related to the curing of concrete pavement.

Prediction of membrane purification by membrane fouling based on mathematic and machine learning models combined with image processing technology

Apples have been widely cultivated due to their multiple functional nutrients such as polyphenols. In this study, polyphenol of apple skins were extracted and purified by ultrasound treatment and membrane filtration, respectively. The effects of feed liquid concentration, transmembrane pressure, and rotational speed on the purification of polyphenols by membrane filtration were mainly investigated. The efficiency of polyphenol purification was analyzed based on the particle deposition effect, steric rejection effect, and pectin sieving effect. Single and multi-stage Hermia models were applied to corroborate the aforementioned theory. The degree of membrane fouling was quantitatively analyzed using a self-written image processing program. The study compared the quantitative prediction models between the degree of membrane fouling and polyphenol purification using mathematical models and two machine learning (ML) models, namely Support Vector Machine Regression (SVR) and Back Propagation Artificial neural networks (BPNN). The degree of membrane fouling and the degree of polyphenol purification were used as input parameters and output parameters of the ML prediction model, respectively. The ratio of the training set (98 data points) and the test set (42 data points) was 7:3. The obtained results showed that the prediction efficiency of BPNN model (R2 =0.99968) outperformed the SVR model (R2 =0.97697), which was better than the mathematical model in terms of prediction performance due to the high generalization ability of the ML model and the high robustness of BPNN. The study provided an effective and accurate method for predicting membrane fouling and filtration purification. Thus, the use of ML as an artificial intelligence technique has a promising future in membrane separation and purification.

Study of Tribological Properties and Evolution of Morphological Characteristics of Transfer Films in PTFE Composites Synergistically Reinforced with Nano-ZrO2 and PEEK Particles.

The materials tribology community has identified that the transfer film attached to the surface of the counterpart metal during the friction process is not only closely related to the filler modification material but also a key factor affecting the tribological properties of polymer composites; however, there is a lack of feasible methods to quantify the characteristics of the transfer film. In this study, Nano-ZrO2 and polyetheretherketone (PEEK) were filled into a PTFE matrix in order to enhance the wear resistance of polytetrafluoroethylene (PTFE). The tribological properties of the modified PTFE composites were tested using a linear reciprocating friction and wear tester, and the entire friction experiment was designed in seven separate stages. Morphological features were extracted and analyzed from photographs of the transfer film acquired by optical microscopy at each friction stage using an image processing program. The thickness and roughness of the transfer film sections were measured using a non-contact profilometer. Abrasive debris were collected, and their morphological features were observed with an electron microscope. The results showed that the synergistic addition of soft PEEK and hard Nano-ZrO2 particles effectively inhibited interlayer slippage between PTFE molecular chains, dramatically reducing the size and yield of abrasive debris, and facilitated the improvement of the thickness and firmness of the transfer film, which significantly enhanced the wear resistance of the PTFE composites (the lowest volumetric wear rate for Nano-ZrO2/PEEK/PTFE was only 1.76 × 10-4 mm3/Nm). Quantitative analyses of the morphological characteristics of the transfer films revealed that the coverage and roundness of the transfer films gradually increase with the friction stroke, while the aspect ratio and texture entropy subsequently decrease gradually. The coverage, area, mean, third-order moments, and consistency of the transfer film strongly correlated with the volumetric wear rate (correlation coefficient |r| > 0.9).

Optimizing the performance of auxetic square tubes under uniaxial compression

Thin-walled tubes are widely used as energy absorbers to increase the crash resistance and safety while maintaining lightness. There has been an increase in interest in the integration of auxetic structures into these tubes. This is due to the better mechanical strength displayed by auxetic structures with negative Poisson’s ratio, particularly in terms of compressive behavior and energy absorption. In this study, a group of square-section tubes with different types of cell structures on their side faces was examined. Under quasi-static compression, the behaviors of thin-walled square tubes with reentrant auxetic and conventional honeycomb were examined numerically and experimentally. In addition, geometric optimization of reentrant cell shape was performed to maximize the compressive loading of the square tubes. First, the compression behaviors of thin-walled square tubes made of polylactic acid (PLA) were examined; these tubes’ side surfaces have both conventional and reentrant auxetic honeycomb cellular patterns. The reentrant auxetic and conventional honeycomb cell architectures were applied together and separately on the side faces of the thin-walled tube, with the identical cell parameters. In order to better understand the deformations, force-displacement curves were examined for four different types of thin-walled square tubes, including tubes with reentrant auxetic and honeycomb cell structures on all side faces and tubes with these structures on opposite sides and adjacent. Using the ANSYS finite element software package and Digimizer image processing programs, the Poisson’s ratio of the reentrant auxetic and conventional honeycomb configurations as well as the maximum compression force of the tubular structures were determined numerically and experimentally. After obtaining the result that the use of the reentrant auxetic structure on the side surfaces of the square tube significantly increased the compression resistance and energy absorption capability of the tube, the optimization of the square tube with the reentrant auxetic structure on all surfaces was examined. The effect of the geometrical parameters such as ligament length, reentrant angle, and cell thickness of the unit-cell on the compression load of the square tube was investigated using an integrated methodology combining numerical simulation and DoE (Design of Experiments) method. The findings show that the tubes combined reentrant auxetic structure exhibits better energy absorption than the conventional honeycomb tubes. It also reveals that the optimum geometric parameters of the reentrant auxetic unit cell are to be the ligament length of 16.358 mm, the ligament angle of 80°, and the ligament thickness of 3 mm.

Investigation of factors enhancing droplets spreading on leaves with burrs.

Spread effect is one of the aspects on deposition quality evaluation of pesticide droplets. It could be affected by many factors such as the microstructure of the target plant leaf surface, physical features of the droplets, and the concentration of spray additives. In this study, using a high-speed photography system, 2.3% glyphosate ammonium salt solution with different concentration of the additive was applied to investigate the impact process of single droplet deposition on the plant leaf surface with burrs. Effect of droplet sizes and velocities on spreading area and dynamic deposition procedure was analyzed using image processing programs. The diffusion factor in the process of droplet spreading was changed over time. The occurrence of bubbles in the droplets was observed in the results. With the bubble generation, the droplet diameter expands and a better diffusion effect is obtained. As a result, better spreading effect was obtained as the droplet diameter was expanded with the generation of bubbles. The significant effects of each physical property of droplets on droplet spreading and the interaction effects between the influencing factors were analyzed. A significant correlation was found between additive concentration, droplet impact velocity, droplet diameters and droplet spreading area. All interactions of concentration:velocity, concentration:diameter, velocity:diameter, and concentration:velocity:diameter had a significant effect on the spreading area of droplets. The study of the factors influencing the process of pesticide droplet impact on the leaf surface contributes to the efficient use of pesticides. Thus, the consumption of pesticides and the resulting impact on the environment can be reduced.

Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program

Nonalcoholic fatty liver disease is rapidly becoming one of the most common causes of chronic liver disease worldwide and is the leading cause of liver-related morbidity and mortality. A quantitative assessment of the degree of steatosis would be more advantageous for diagnostic evaluation and exploring the patterns of disease progression. Here, multiphoton microscopy, based on the second harmonic generation and 2-photon excited fluorescence, was used to label-free image the samples of nonalcoholic fatty liver. Imaging results confirm that multiphoton microscopy is capable of directly visualizing important pathologic features such as normal hepatocytes, hepatic steatosis, Mallory bodies, necrosis, inflammation, collagen deposition, microvessel, and so on and is a reliable auxiliary tool for the diagnosis of nonalcoholic fatty liver disease. Furthermore, we developed an image segmentation algorithm to simultaneously assess hepatic steatosis and fibrotic changes, and quantitative results reveal that there is a correlation between the degree of steatosis and collagen content. We also developed a feature extraction program to precisely display the spatial distribution of hepatocyte steatosis in tissues. These studies may be beneficial for a better clinical understanding of the process of steatosis as well as for exploring possible therapeutic targets.

MRC2020: improvements to Ximdisp and the MRC image-processing programs.

The great success of single-particle electron cryo-microscopy (cryoEM) during the last decade has involved the development of powerful new computer programs and packages that guide the user along a recommended processing workflow, in which the wisdom and choices made by the developers help everyone, especially new users, to obtain excellent results. The ability to carry out novel, non-standard or unusual combinations of image-processing steps is sometimes compromised by the convenience of a standard procedure. Some of the older programs were written with great flexibility and are still very valuable. Among these, the original MRC image-processing programs for structure determination by 2D crystal and helical processing alongside general-purpose utility programs such as Ximdisp, label, imedit and twofile are still available. This work describes an updated version of the MRC software package (MRC2020) that is freely available from CCP-EM. It includes new features and improvements such as extensions to the MRC format that retain the versatility of the package and make it particularly useful for testing novel computational procedures in cryoEM.

Building Intelligence in the Mechanical Domain—Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Tasks

Herein, the cognitive capability of a simple, paper‐based Miura‐ori—using the physical reservoir computing framework—is experimentally examined to achieve different information perception tasks. The body dynamics of Miura‐ori (aka its vertices displacements), which is excited by a simple harmonic base excitation, can be exploited as the reservoir computing resource. By recording these dynamics with a high‐resolution camera and image processing program and then using linear regression for training, it is shown that the origami reservoir has sufficient computing capacity to estimate the weight and position of a payload. It can also recognize the input frequency and magnitude patterns. Furthermore, multitasking is achievable by simultaneously applying two targeted functions to the same reservoir state matrix. Therefore, it is demonstrated that Miura‐ori can assess the dynamic interactions between its body and ambient environment to extract meaningful information—an intelligent behavior in the mechanical domain. Given that Miura‐ori has been widely used to construct deployable structures, lightweight materials, and compliant robots, enabling such information perception tasks can add a new dimension to the functionality of such a versatile structure.

Real-time seam tracking during narrow gap GMAW process based on the wide dynamic vision sensing method

Welding torch horizontal seam tracking is a crucial condition to realize automatic welding of narrow gap gas metal arc welding (NG-GMAW) robots. In the present study, a real-time welding seam tracking technology based on the passive vision sensor is proposed. To this end, a wide dynamic range (WDR) vision sensor is used to capture real-time welding images. In order to realize real-time identification of the welding torch center deviation in the process of swinging arc in a welding bead, a welding seam tracking algorithm based on the window information fusion (WIF) is proposed. In this regard, the local feature moving window recognition (LMWR) algorithm is applied to extract the groove center. Based on the improved welding image processing program, the weld pool center and welding wire center are prepared for seam tracking. In this regard, considering the trifling variation of groove and weld pool center, the welding horizontal deviation is obtained by combining them with welding wire center calculation. Aiming at establishing a correlation between consecutive images, the Kalman filter is used to estimate the deviation optimally. The tracking algorithm is successfully verified in the weld bead with a horizontal deviation, and the tracking accuracy of ±0.47 mm is achieved. The performed analyses demonstrate that the developed algorithm meets the requirements of real-time seam tracking in the GMAW process of the welding robot.

Determination of Flap Survival Isolated From Wound Bed Vasculature Using a Murine Axial Flap Model.

Background: Axial pattern flaps are a common reconstructive option following resection of soft tissue malignancies. We determine the early dependence of an axial flap on wound bed vasculature by isolating the underlying wound bed and depriving contact with the overlying flap. Materials and Methods: Mice were divided into 5 groups: No silicone (n = 7), silicone in the proximal 50% of the wound bed (n = 8), silicone in the distal 50% of the wound bed (n = 5), silicone over the full length of the wound bed with pedicle preservation (n = 5), and silicone over the full length of the wound bed with pedicle sacrifice (n = 5). The pedicle was the lateral thoracic artery. Daily photographs were taken, and the percent of viable flap was determined using ImageJ© software (public domain JAVA image processing program, National Institute of Health, Bethesda, MA). Percent flap viability for each group was compared to the no silicone group, which acted as the reference. Results: Mean differences in percent flap necrotic area (with 95% confidence interval) compared to the no silicone group were -0.15% (-15.09 to 14.09), 2.07% (-5.26 to 9.39), 2.98% (-10.98 to 16.94), and 14.21% (0.48 to 27.94) for the full-length silicone with preserved pedicle, proximal silicone, distal silicone, and full-length silicone with sacrificed pedicle groups, respectively. The full-length silicone with sacrificed pedicle group had a significant difference in flap viability (P = .045) compared to the no silicone group. Conclusion: We investigate the role of the wound bed vasculature in a murine axial flap model and demonstrate that the wound bed vasculature is not essential for early distal flap survival.

An experimental study on quenching of metallic spheres in seawater

Motivated by quenching of melt droplets and debris particles in seawater during a hypothetical severe accident of light water reactors (LWRs), the quenching process of stainless-steel spheres in a seawater pool was investigated in the present study. The polished spheres were pre-heated up to 1000℃ in an induction furnace with inserted atmosphere, and then immersed into the subcooled water pool in a chamber made of transparent quartz. A thermocouple was embedded in the center of the sphere to measure the history of the sphere’s temperature, while a high-speed camera was employed to record the quenching process and vapor film dynamics. Quantitative data, e.g. film thickness and oscillation, of the vapor film evolution during the quenching process were obtained through an image processing program developed on the MATLAB platform.The experimental results indicated that the quenching rate was higher in seawater than in deionized water, and the vapor film collapsed at a temperature higher than the Leidenfrost temperature in deionized water. The trend appeared more significant with increasing subcooling of water. The comparison of the quenched spheres suggested the surface of the sphere in seawater achieved higher degree of discoloration and roughening than that in deionized water, probably due to the additives of salt which change water properties. The image processing and analysis revealed that the vapor film had different thickness profile along the upper and lower hemispheres, and the averaged film thickness was smaller in seawater than in de-ionized water during the stage of stable film boiling. The vapor film was thinning and oscillating with time, and its fluctuations appeared different frequencies and amplitudes at the upper and lower locations, which may explain the mechanism of the earlier collapse of vapor film in the quenching process of a high-temperature sphere in seawater.

Improving behavioral test data collection and analysis in animal models with an image processing program

Behavioral studies are commonly used as a standard procedure to evaluate anxiety and depression in animal models. Recently, different methods have been developed to improve data collection and analysis of the behavioral tests. Currently available methods, including manual analysis and commercially available products, are either time-consuming or costly. The objective of this study was to improve the collection and analysis of behavioral test data in animal models by developing an image processing program. Eleven behavioral parameters were evaluated by three different methods, including (i) manual detection, (ii) commercially available TopScan software (CleverSys Inc, USA), and (iii) In-housed-developed Advanced Move Tracker (AMT) software. Results obtained from different methods were compared to validate the accuracy and efficiency of AMT. Results showed that AMT software provides highly accurate and reliable data analysis compared to other methods. Less than 5% tolerance was reported between results obtained from AMT compared to TopScan. In addition, the analysis processing time was remarkably reduced (68.3%) by using AMT compared to manual detection. Overall, the findings confirmed that AMT is an efficient program for automated data analysis, significantly enhancing research outcomes through accurate analysis of behavioral test data in animal models.

Scientific Visualization for Interrogation of Results in Lighting Simulation System

Lighting modeling software packages often include a tool for processing and investigation of two-dimensional images that are the results of modeling. Functionality of these tools is usually minimal one and often consists of mapping of resultant images into monitor screen only. There are general image viewers and image processing programs. But in practice they either do not contain required functionality, or are so superfluous that result postprocessing becomes inconvenient with them. Therefore we had to implement own viewer that processes high dynamic range images generated by the lighting simulation and realistic computer graphics system as well as visualizes supplementary simulation information needed for engineer analysis. Lighting simulation module transfers to our viewer the generated image in physical values together with supplementary data. These data has per pixel nature and form additional layers of images. Our image processing module provides brightness high dynamic range compression for rendering of images generated with lighting modeling methods including stochastic ones, analysis of the image generation algorithms using additional data layers, applying additional visual effects for improving images appearance, and export of processed images to commonly used formats.

Automated Driver Drowsiness Detection

This project uses image processing and Python programming language to create an automatic sleepiness detection system for drivers. The system's objective is to develop an algorithm that can reliably gauge a driver's sleepiness under various circumstances by using real-time grayscale photographs. The driver will be observed by the system as it scans their face and eyelids for hypo vigilance, which is a precursor to tiredness. To properly determine the driver's level of sleepiness, the system entails three steps: feature selection, eye-pair state detection, and decision-making. The algorithm will differentiate between the two states on a collection of captured photos of both tired and awake drivers. To identify sleepiness in drivers, facial feature recognition algorithms has been employed, with an emphasis on the eye pair. Images will be taken with a mounted camera. For the system to successfully be integrated into current driver assistance systems, it will be measured on how well it is able to identify tiredness. The project's importance stem from its ability is to increase road safety by identifying driver sleepiness, a major contributing factor to accidents on the road. In conclusion, this research will significantly impact road safety by tackling the problem of accidents caused by drowsiness.

Effects of a gasoline particulate filter on the physicochemical characteristics of particulate matter from a gasoline engine

Gasoline particulate filters (GPFs) are being used increasingly in gasoline direct-injection engines because they can reduce particle emissions and allow emission regulations to be met. Therefore, understanding the particles' physicochemical properties can help with optimizing the post-processing systems and engine calibration. In this study, particles were collected both pre- and post-GPF using a Dekati® low-pressure impactor and a quartz-fiber filter membrane. High-resolution transmission electron microscopy was used to observe the morphologies of the particles, the fractal dimension was used to quantify the aggregate structure, and an image-processing program developed in MATLAB was used to analyze the nanostructures of the primary particles. Raman spectroscopy was used to study the order degree of the particles’ carbon crystal arrangement, and Fourier transform infrared spectroscopy was used to assess the changes in their surface functional-group content. After the particles were graded according to particle size, it was found that (i) the fractal dimension of all size levels and (ii) the average size of the primary particles were both smaller post-GPF than pre-GPF. Post-GPF, there was a higher proportion of nucleated particles, the particle fringe length was shorter, the tortuosity and separation were both greater, the particles were more disordered, the ratio of C–H to C–O was greater, and the proportion of organic composition of the particles and their oxidation activity were both increased.

Identification and counting of fish targets using adaptive resolution imaging sonar.

Fish are a critical component of marine biology; therefore, the accurate identification and counting of fish are essential for the objective monitoring and assessment of marine biological resources. High-frequency adaptive resolution imaging sonar (ARIS) is widely used for underwater object detection and imaging, and it quickly obtains close-upvideo of free-swimming fish in high-turbidity water environments. Nonetheless, processing the massive data output using imaging sonars remains a major challenge. Here, the authors developed an automatic image-processing programme that fuses K-nearest neighbour background subtraction with DeepSort target tracking to automatically track and count fish. The automatic programme was evaluated using four test data sets with different target sizes and observation ranges and differently deployed sonars. According to the results, the approach successfully counted free-swimming fish targets with an accuracy index of 73% and a completeness index of 70%. Under appropriate conditions, this approach could replace time-consuming semi-automatic approaches and improve the efficiency of imaging sonar data processing, while providing technical support for future real-time data processing.

A Simple Technique to Assay Locomotor Activity in Drosophila.

Drosophila melanogaster is an ideal model organism for studying various diseases due to its abundance of advanced genetic manipulation techniques and diverse behavioral features. Identifying behavioral deficiency in animal models is a crucial measure of disease severity, for example, in neurodegenerative diseases where patients often experience impairments in motor function. However, with the availability of various systems to track and assess motor deficits in fly models, such as drug-treated or transgenic individuals, an economical and user-friendly system for precise evaluation from multiple angles is still lacking. A method based on the AnimalTracker application programming interface (API) is developed here, which is compatible with the Fiji image processing program, to systematically evaluate the movement activities of both adult and larval individuals from recorded video, thus allowing for the analysis of their tracking behavior. This method requires only a high-definition camera and a computer peripheral hardware integration to record and analyze behavior, making it an affordable and effective approach for screening fly models with transgenic or environmental behavioral deficiencies. Examples of behavioral tests using pharmacologically treated flies are given to show how the techniques can detect behavioral changes in both adult flies and larvae in a highly repeatable manner.