Grayscale Threshold Research Articles

Research on Femtosecond-Laser Pulse-Width Measurement Based on LabVIEW

In this paper, we propose a measurement system based on single autocorrelation technology and combined with LabVIEW software platform to realize the real-time online measurement of the femtosecond-laser pulse width. The system uses an experimental device based on the Mach–Zehnder interferometer, where the second-harmonic signal of femtosecond laser is obtained by the nonlinear effect of light and nonlinear material; the linear grayscale conversion, median filtering, and threshold segmentation are also applied to the second-harmonic signal. The image centroid, autocorrelation curve, and femtosecond-laser pulse width are obtained, using LabVIEW software. In the experiment, a seed laser source with a central wavelength of 800 nm is used as a test object, and the pulse width is measured to be equal to 261 fs.

Properties of calcium aluminate blended cement incorporating iron-rich slag: Evolution over a curing period of 1 year

With an outlook directed towards circular economy, the valorization of municipal waste streams and industrial residues has recently conveyed a variety of novel industrial by-products to various applications such as supplementary cementitious materials (SCM) in cement blends or as precursors to inorganic polymers. Despite the synergistic benefits on recycling, reducing the cost and the carbon footprint of cements, the use of such non-conventional SCM is often limited to ordinary Portland cement (OPC)-based formulations. This study investigates the properties of a calcium aluminate cement (CAC)-based blend incorporating 30 wt% of iron (Fe)-rich slag produced at pilot scale from an industrial lead–zinc production. Compressive and flexural strength (EN 196-1 standard mortars), setting time, dimensional stability (Walter + Bai shrinkage measuring test), early hydration reactions (isothermal calorimetry), and phase assemblage evolution (XRD and TGA) were followed from 1 day to 1 year of curing period for both the slag-containing- and a corresponding reference cement formulation. Additionally, a fast non-destructive technique for quantifying the degree of slag hydration is demonstrated using a combination of X-ray computed tomography (XCT) and volume analysis based on grayscale threshold segmentation. The results from the different techniques suggest the long term (>28 days) reactivity of the slag with the slag-containing mortars attaining a comparable compressive strength of 39 MPa versus 41 MPa of the corresponding reference mortars at 90 days. Likewise, the prominent contribution of the slag to the hydration reactions is manifested by the differences in the evolution of the phase assemblage of the two formulations. The degree of slag hydration was calculated to progressively increase over time reaching up to 49% after 1 year of hydration based on the XCT scans. These results along with the long term dimensional stability of the slag-containing formulation support the potential for valorization of the Fe-rich slag as SCM in the CAC-based blend.

Segmentational color map analysis to identify retinal detachment

The recent perilous times entails the importance of good health for humans. This can be pertaining the maintenance of good health in various organs of the human body. With the increase of digital platforms, and the necessity to stay longer hours with gadgets and electronic devices, the human eye takes a toll in terms of absorbing radiations that maybe harmful. An imperative check of the eye is essential from time to time, as the luminous membrane that aids in vision needs to hold firm to the various components within itself. Although there are various treatments associated with the detection of eye detriments, several gremlins tend to loom at large. These eye diseases can arise from numerous reasons ranging from genetic disorders to accidents and vision loss due to stimulated injuries, infections and dysfunctional development of tissues/cells/nerves within the eye. Retinal detachment (RD) is one of the profound problems that persist amongst many individuals scaling over a diverse range of ages. The risk in relevance to untreated detachment of the eye leads to purblind and sometimes complete loss of vision. The previous paper concerning retinal detachment of human eye has focused on various algorithmic and post-processing approaches, but failed to identify the origination and symptoms that could aid in meticulous diagnosis. The indagation in this paper pivots on the unsheathing of attributes that explicates the disassociation of the retina from the underlying layers of the eye using the fundus image with cost-effectiveness and swifter analysis. An important characteristic that is emphasized in this study is the segmentation of eye floaters in the vitreous fluid of the eye. These eye floaters are color mapped to identify the presence of detached tissues in the eye. The histogram analysis using the grayscale thresholding value further aids in providing a detailed distinction of the normal eye from the detached eye. The simulations are carried out in MATLAB, and the results have been obtained successfully.

Effect of spray angle onto the microstructure of EB-PVD enabled 8YSZ thermal barrier coatings

Abstract The microstructure plays an important role in the durability and performance of the Thermal Barrier Coatings (TBCs). The TBCs were deposited on Ti-6Al-4 V substrate with NiCrAlY bond coat using APS and 8YSZ using in-house EB-PVD. The paper presents the effect of spray angle onto the microstructural and mechanical properties of 8YSZ in detail. The surface microstructural and elemental composition are examined using SEM with EDS. The coating porosity was examined by SEM and ImageJ using the grayscale threshold technique. Also, the mechanical properties like hardness, surface roughness, and thickness were measured by indentation, surface profilometer, and optical microscopy in combination with ImageJ. The results show 90° TBC with the uniform structure in the presence of a few pores and cracks compared to 60° TBC. In 60° TBC, the dissimilar grain growth and elongated grains with average size 300 nm compared to 90° TBC grain size 150 nm was observed. In 60° TBC, porosity with 20.65% more was present which contributes to large shadow region leading to high porosity. Also, the decrease in coating hardness with 5% was observed with an inclined spray angle. In 60° TBC, the rough and non-uniform surface was obtained, but the overall coating thickness was almost similar for both the spray angle condition.

Segmentation using fuzzy cluster‐based thresholding method for apple fruit sorting

Apple fruit sorting has been an important postharvest process carried on for the sorting of diseased apple fruits. A fuzzy cluster-based thresholding (FCBT) method for segmenting the region of interest from an apple image has been proposed for sorting apples in this study. As the first step, the acquired RGB colour image of an apple fruit was converted into a greyscale image. Then, five different fuzzy cluster bins with overlapped pixel ranges were taken and greypixel values were binned into them. A cluster with the maximum number of pixels was selected for calculating the threshold value. The region of interest from the apple image was then segmented using the proposed FCBT value. Features extracted from the segmented images were given as input to a fully-connected deep neural network for a classification. The performance of the FCBT method was compared with similar greyscale thresholding methods like Otsu's and Kapur's methods. The visual segmentation accuracy and the execution speed showed that the FCBT outperformed the other methods in segmenting the diseased area. A fully-connected deep neural network model with the FCBT image extracted features as input values gave a 98.33% accuracy rate in sorting the apple images.

Infrared Thermal Imaging for Intelligent Leakage Detection in Underground Integrated Pipe Corridors

Abstract Water leakage is a major problem in underground integrated corridors. Research on damage detection in pipelines using automatic techniques has yielded considerably high detection accuracy. Many proposals in this domain show the presence of leakage only when a certain degree of damage occurs. However, in practical scenarios, the corridor managers of a governing body need to take effective action as soon as a leak is detected. This study makes three contributions to relevant research. First, a state-of-the-art intelligent leakage detection method is proposed for underground integrated corridors using infrared thermal imaging. Considering the difference in terms of specific heat capacity between water and the material of the pipe, when slightly heated, cracks in the loose water-pipe interface can be identified in two-dimensional infrared images. The crack-causing leakage can be extracted via the temperature difference between the leak and the ambient field through image processing based on the grayscale threshold segmentation technique and fractal feature theory. Finally, experiments show that the proposed method can achieve an accuracy of up to 90 %, and compensates well for deficiencies in the traditional method. It can implement intelligent leakage detection in underground integrated corridors at low cost with high efficiency.

Blue-Ice Extraction and Classification in Antarctica Using MOA Images

Zhang, X.; Zhou, C.; Yuan, L., and E, D., 2020. Blue-ice extraction and classification in Antarctica using MOA images. In: Yang, D.F. and Wang, H. (eds.), Recent Advances in Marine Geology and Environmental Oceanography. Journal of Coastal Research, Special Issue No. 108, pp. 188–192. Coconut Creek (Florida), ISSN 0749-0208.Using Moderate Resolution Imaging Spectroradiometer (MODIS) Mosaic of Antarctica (MOA) images, areas of Antarctic blue ice were extracted and classified based on the grayscale threshold value of Band 1 MODIS images and the threshold of the surface snow grain size in Band 1 and Band 2 MODIS images. The MOA-based blue-ice area extraction method was verified by tests in blue-ice areas on Grove Mountains, and the MOA-based blue-ice classification method was verified by tests on Queen Maud Land. Highly reliable Antarctic blue-ice distribution maps were obtained in this study, and the blue-ice extent in Antarctica is 188,857–226,628 km2.

Quantification of late gadolinium enhancement cardiovascular MRI in patients with coronary artery chronic total occlusion

To determine the most accurate and reproducible semi-automated greyscale thresholding technique for quantifying late gadolinium enhancement (LGE) in cardiovascular magnetic resonance imaging (CMRI), by using positron-emission tomography (PET) as the reference standard in patients with coronary artery chronic total occlusion (CTO). LGE in CMRI, single-photon-emission computed tomography (SPECT), and PET were performed within 1 week in each of 63 patients with known CTO. The presence and quantity of LGE were determined with greyscale thresholds of 2, 4, 5, 6, and 8 standard deviations (SDs) above the mean signal intensity for normal remote myocardium and full width at half maximum (FWHM). The infarcted myocardium was delineated by PET. Sixty-three patients and 1,008 segments were analysed. Based on patient analysis, with PET as the reference standard, the 5 SD method yielded the strongest correlation (r=0.85, p<0.0001) compared with the 2 SDs (r=0.42), 4 SDs (r=0.73), 6 SDs (r=0.81), 8 SDs (r=0.71), and FWHM (r=0.69; p<0.001 for all comparisons). The 5 SDs threshold quantification showed high interobserver and intra-observer agreement (intraclass correlation coefficient [ICC]=0.90, p<0.0001; ICC=0.93, p<0.0001, respectively). Semi-automated LGE CMRI greyscale thresholding with 5 SDs above the mean signal intensity for normal remote myocardium yields the strongest correlation to the extent of LGE identified using PET and is highly reproducible in patients with CTO.

An improved cuckoo search algorithm for multi-level gray-scale image thresholding

In decades, Yang’s cuckoo search algorithm has been widely developed to select the optimal threshold of bi-level image threshoding, but the amount of computation of which increases exponentially with multi-level thresholding. To reduce the computation quantity, the iterative step size is adaptively decided by its fitness values of the current iteration without using the Levy distribution in this study. The modification may cause the solution drops into the local optima during the later period. Therefore, the constant discovery probability pa is automatically changed relating to the current and total iterations. And then, to verify segmentation accuracy and efficiency of the proposed method, an adaptive cuckoo search algorithm proposed by Naik and Yang’s cuckoo search algorithm are included to test on several gray-scale images. The results show that the proposed algorithm is expert in selecting optimal thresholds for segmenting gray-scale image.

Sub-pixel Center Extraction Method for Line structured Light Stripe

The extraction of line structured light center is a key technology in line structured light measurement system. The precision of light stripe extraction affects the accuracy of the measurement system. Due to the differences of the materials and quality of the laser device, the light stripes is variable in different position that the energy distribution and morphological characteristics are easily changed. It is difficult to extract the center of the stripes by using traditional light stripe extraction methods accurately. Our study proposes an extraction algorithm for the light stripe center. First of all, separating a single stripe from the image according to the morphological characteristics of the light stripe, and the effective region of the light stripe was initially determined. Then, using the grayscale attribute method as well as the grayscale threshold method to determine the region of interest in the center of the light stripe. Finally, the sub-pixel center of the light stripe in the regions of interest was calculated by the grayscale barycenter method. The experimental results showed that the algorithm in the study can be used to extract light stripes with changeable characteristics. It is more accurate and stable comparing with the traditional extraction algorithm of light stripe center.

The characteristic analysis of temperature sensor based on a fabricated microstructure fiber by digital image processing technique and finite element method

A temperature sensor based on a Sagnac interferometer by the actual microstructure fiber (MSF) selectively filled with ethanol has been designed in this paper. We obtained the vectorized cross-section of MSF using the method of the digital image processing technique and the finite element method. This method can model the actual cross section structure of MSF rapidly by gray scale processing, filtering, threshold, and edge detection and be applied to the calculation and simulation of the actual MSF perfectly. The air holes on both sides of the core were filled with ethanol to improve the birefringence of the MSF. The simulation result showed that the dip wavelength in transmission spectrum has a blue-shift when the temperature increasing. The average sensitivity can be up to 1 nm °C−1 as the temperature rises from 25 °C to 75 °C. It can be tested in a wide temperature range, which plays a profound role in practical application.

Dynamic image analysis of transparent particles released during the simulated use test of cardiovascular devices

Abstract For product approval of coated cardiovascular devices, the assessment of particle release is essential. Particularly challenging are delivery systems equipped with hydrophilic coatings releasing highly transparent particles. The aim of this study was to compare two different methods of particle counting, namely the light obscuration method and the dynamic image analysis (DIA), with respect to optical transparent particles. The particles were collected during the simulated use of cardiovascular catheters and analysed in suspension with a dynamic imaging device (FlowCam, Fluid Imaging Technologies). Particles were detected by a greyscale threshold and imaged to analyse their shape and transparency. The statistical influence of the threshold on particle counts and size distribution was determined and compared to light obscuration particle counting (Model 9703 with sensor HRLD 400CE, HIAC ROYCO). The light obscuration method provided lower particle counts in suspensions containing a high amount of transparent particles. The lower the detection threshold, the higher the particle counts were. In conclusion, it is important to adapt the threshold value for samples that are expected to contain a high amount of transparent particles. DIA may be suggested as a valuable additional method for particulate analysis.

An Image-Guided Intrascaffold Cell Assembly Technique for Accurate Printing of Heterogeneous Tissue Constructs.

For tissue engineering and regenerative medicine, creating thick and heterogeneous scaffold-based tissue constructs requires deep and precise multicellular deposition. Traditional cell seeding strategies lack the ability to create multicellular tissue constructs with high cell penetration and distribution, while emerging strategies aim to simultaneously combine cell-laden tissue segments with scaffold fabrication. Here we describe a technique that allows for three-dimensional (3D) intrascaffold cell assembly in which scaffolds are prefabricated and pretreated, followed by accurate cell distribution within the scaffold using an image-guided technique. This two-step process yields less limitation in scaffold material choice as well as additional treatments, provides accurate cell distribution, and has less potential to harm cells. The image processing technique captures a 2D geometric image of the scaffold, followed by a series of processes, mainly including grayscale transformation, threshold segmentation, and boundary extraction, to ultimately locate scaffold macropore centroids. Coupled with camera calibration data, accurate 3D cell assembly pathway plans can be made. Intrascaffold assembly parameter optimization and complex intrascaffold gradient, multidirectional, and vascular structure assembly were studied. Demonstration was also made with path planning and cell assembly experiments using NIH3T3-cell-laden hydrogels and collagen-coated poly(lactic-co-glycolic acid) (PLGA) scaffolds. Experiments with CellTracker fluorescent monitoring, live/dead staining, and phalloidin-F-actin/DAPI immunostaining and comparison with two control groups (bioink manual injection and cell suspension static surface pipetting) showed accurate cell distribution and positioning and high cell viability (>93%). The PrestoBlue assay showed obvious cell proliferation over seven culture days in vitro. This technique provides an accurate method to aid simple and complex cell colonization with variant depth within 3D-scaffold-based constructs using multiple cells. The modular method can be used with any existing printing platform and shows potential in facilitating direct spatial organization and hierarchal 3D assembly of multiple cells and/or drugs within scaffolds for further tissue engineering studies and clinical applications.

Hybrid radial basis function with firefly algorithm and simulated annealing for detection of high cholesterol through iris images

Cholesterol is a lipid (fat) produced by the liver and is required to build and maintain cell membranes. Cholesterol is also important for the metabolism of fat soluble vitamins. This important lipid is found in human blood. Excess cholesterol (high cholesterol) can cause health problems such as being a factor of coronary heart disease that responsible for the heart attacks, liver or kidney disease. Observation of iris pattern can detect several types of diseases, one of which is high cholesterol. The purpose of this research is to detect whether someone is exposed to high cholesterol or not, through iris images based on firefly algorithm, simulated annealing, and radial basis function. Firefly algorithm and simulated annealing are used in the unsupervised learning process in radial basis function neural networks. The stages of high cholesterol detection process are images processing namely grayscale process, thresholding, histogram equalization, segmentation, and detection process is using radial basis function neural network. The percentage success rate of the recognition pattern of iris images for detecting high cholesterol is 89%.

Analysis of peritumoral hyperintensity on pre-operative T2-weighted MR images in glioblastoma: Additive prognostic value of Minkowski functionals.

ObjectivesThe extent of peritumoral tumor cell infiltrations in glioblastoma contributes to poor prognosis. We aimed to assess additive prognostic value of Minkowski functionals in analyzing heterogeneity of peritumoral hyperintensity on T2WI in glioblastoma patients.MethodsClinical data (age, sex, extent of surgical resection), O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and pre-operative T2WI of 113 pathologically confirmed glioblastoma patients (from our institution, n = 61; from the Cancer Imaging Archive, n = 52) were retrospectively reviewed. The patients were randomly grouped into a training set (n = 80) and a test set (n = 33). Peritumoral T2 hyperintensity was manually segmented and Minkowski functionals—a texture analysis method capturing heterogeneity of MR images—were computed as a function of 11 grayscale thresholds. The Cox proportional hazards models were fitted with clinical variables, Minkowski functionals features as well as both combined. The risk prediction performances of the Minkowski functionals and combined models were validated on a separate test dataset. The sex-specific survival difference of the entire cohort was analyzed according to MGMT methylation status via Kaplan-Meier survival curves.ResultsThirty-three Minkowski features (11 area, 11 perimeter and 11 genus) for each patient were acquired giving a total of 3729 features. Cox regression models fitted with clinical data, Minkowski features, and both combined had incremental concordance indices of 0.577 (P = 0.02), 0.706 (P = 0.02) and 0.714 (P = 0.01) respectively. The prediction error rate of the combined model—having clinical and Minkowski features—was lower than that of Minkowski functionals model (0.135 and 0.161, respectively) when validated on a test dataset. No sex-specific survival difference was found according to MGMT methylation status (male, P = 0.2; female, P = 0.22).ConclusionsMinkowski functionals features computed from peritumoral hyperintensity can capture heterogeneity of glioblastoma on T2WI and have additive prognostic value in predicting survival, demonstrating their potential in complementing currently available prognostic parameters.

Pore structure characterization and permeability prediction of coal samples based on SEM images

The pore structure of coal reservoirs determines the reserves of coalbed methane, and the gas permeability determines the level of the production capacity. In this study, the SEM images of coal samples were analyzed by various means. First, the grayscale threshold of binarization of the coal sample image is determined by a suitable algorithm. Comparing several different algorithms, the porosity based on Yen algorithm is closer to the results of vacuum saturation method and nuclear magnetic resonance (NMR) (8.35% vs. 7.51% vs. 8.92%). Further, the pore size distribution (PSD) of the coal sample is obtained according to discrete and continuous algorithms. By comparing the SEM results with the NMR results, it is found that the calculation results based on the continuous algorithm (CPSD) are better than the discrete algorithm (DPSD) and closer to the NMR results. For the effect of scale, we found that the image resolution has a certain influence on the minimum pore size characterized, such as sample C1: 0.29 μm ( × 1000) vs 0.58um ( × 500). At high resolution, more micro-pores are observed. Further, we predict the permeability of coal samples based on SEM images. It is found that the calculation results based on the continuous algorithm and the Hagen–Poiseuille equation are closer to the measured values (e.g., 16.97 (DPSD) vs. 0.45(CPSD) vs. 0.59 mD (Lab), sample C2, magnification of × 1000). In general, this method can effectively evaluate the pore structure characteristics and permeability of coal samples.

Human Inner-ear Malformation Types Captured in 3D.

Capture the human inner-ear malformation types in 3D by segmenting the inner-ear structures from clinical CT (computed tomography) and MR (magnetic resonance) image datasets. Volumetric analysis was done to find the variations in the volume of cochlear part alone from complete inner-ear followed by 3D printing from the 3D segmented models. Using 3D slicer freeware, the complete inner-ear structures were segmented from anonymized CT and MR image by setting a tight grey-scale threshold to avoid capturing unwanted structures followed by volumetric analysis of the cochlear part alone. 3D printing was done using Form labs desktop 3D printer. We identified 2x normal anatomy (NA) cochlea, 1x enlarged vestibular aqueduct syndrome (EVAS), 3x incomplete partition (IP) type-I, 4x IP type-II, 3x IP type-III, 5x common cavity (CC) and 5x cochlear hypoplasia (CH). 3D segmented models along with the 3D printed models showed huge variation in size, shape and the anatomy among the image data-sets analyzed. Volumetric analysis showed that on average, volume of CC was above 150mm3, volume of CH fell below 80mm3, Volume of NA, EVAS and IP-I were all around 85-105mm3 whereas the volume of IP-II was around 50mm3. Visualizing human inner-ear malformation types in 3D both as computer models and as 3D printed models is a whole-new experience as demonstrated in this study. The volumetric analysis showed a huge variation among the volume of cochlear part alone among the malformation types.

Rock Characterization Using Gray‐Level Co‐Occurrence Matrix: An Objective Perspective of Digital Rock Statistics

AbstractModeling flow and transport in porous media using pore‐scale modeling is reliant on rock properties derived from digital rock images using segmentation techniques. These digital rock images obtained using computed tomography incorporate the variation in the intensity of phases depending on the attenuation of X‐rays. A standard technique is the segmentation of tomographic images based on user‐selected grayscale thresholding, allowing the identification of different phases. This threshold is subjective based on the operator and results in loss of essential information about the grayscale variation after segmentation. This paper implements the gray‐level co‐occurrence matrix (GLCM) incorporating the full range of grayscale information. The GLCM captures the relative occurrence of grayscale values in a spatial map. These maps show visually connected/disconnected populations of different phases such as pore space, quartz grains, minerals, and other features. We show that each rock has its own GLCM signature depending on the variations in gray‐level intensities. Several statistical measures are calculated: (1) GLCM contrast describing local variation in the gray‐level intensities, (2) GLCM angular second moment, describing the rock homogeneity; (3) GLCM mean, describing weighted average of the probability of occurrence of features based on their location on the GLCM map; and (4) GLCM correlation, measuring the linear dependencies of grayscale values and the degree of (an) isotropy in the micro–computed tomographic images of each of the rock types. The GLCM method provides a pathway to alleviate user biases and allow automation of micro–computed tomography analyses.

Vision-based position and pose determination of non-cooperative target for on-orbit servicing

For finding an effective measurement for space non-cooperative targets in close distance, a vision-based position and pose determination algorithm of non-cooperative target for on-orbit servicing is investigated. First, the satellite-rocket docking ring’s region is separated from the background environment by a selected grayscale thresholding method and the Canny operator algorithm is used to extract the edge of the satellite-rocket docking ring. Furthermore, the mathematical alignment of the image plane and binocular stereo matching are used to obtain the correspondence of 3D points. Finally, the model of 3D reconstruction is established to determine the relative position and pose of the satellite-rocket docking ring. The ground simulation test shows that our method can measure the relative position and pose of the satellite-rocket docking ring effectively. The precision of the relative position is 0.001 m and that of the relative attitude is 0.1 deg., which satisfies the requirements of the relative measurement for non-cooperative target in extra-close range.

Research on feature extraction and segmentation of rover wheel imprint

The wheel imprint photograph of the rover contains important information such as wheel motion parameters, soil characteristic parameters and movement status of the rover. Segmenting the wheel imprint area from the photograph is an important prerequisite for feature extraction and parameter identification. Traditional image segmentation cannot take both speed and precision into account because they are based on a wide range of image object attributes, such as grayscale threshold, color, texture, gradient, contrast, shape and size. This paper presents an image segmentation method based on the wheel imprint feature. Compared to other common graphics segmentation methods, the morphological characteristics and frequency domain characteristics of the wheel imprint are found out by analyzing the mechanism of the wheel–terrain interaction process, and the eigenvector is also constructed. In the wheel trace feature space, the clustering algorithm is used to divide the image into the trace area and the non-trace area. The segmentation accuracy and processing speed were used to evaluate the algorithm. The experimental results show that the developed algorithm based on the characteristics of wheel imprint formation mechanism is more accurate and efficient than the traditional method.