In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers a...In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.展开更多
This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(...This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(XRD)-based DIP method effectively analyzed the mineral composition contents and spatial distributions of granite. During the particle flow code(PFC2D) model calibration phase, the numerical simulation exhibited that the uniaxial compressive strength(UCS) value, elastic modulus(E), and failure pattern of the granite specimen in the UCS test were comparable to the experiment. By establishing 351 sets of numerical models and exploring the impacts of mineral composition on the mechanical properties of granite, it indicated that there was no negative correlation between quartz and feldspar for UCS, tensile strength(σ_(t)), and E. In contrast, mica had a significant negative correlation for UCS, σ_(t), and E. The presence of quartz increased the brittleness of granite, whereas the presence of mica and feldspar increased its ductility in UCS and direct tensile strength(DTS) tests. Varying contents of major mineral compositions in granite showed minor influence on the number of cracks in both UCS and DTS tests.展开更多
The macro mechanical properties of materials with characteristics of large scale and complicated structural composition can be analyzed through its reconstructed meso-structures.In this work,the meso-structures of tal...The macro mechanical properties of materials with characteristics of large scale and complicated structural composition can be analyzed through its reconstructed meso-structures.In this work,the meso-structures of talus deposits that widely exist in the hydro-power engineering in the southwest of China were first reconstructed by small particles according to the in-situ photographs based on the self-adaptive PCNN digital image processing,and then numerical direct shear tests were carried out for studying the mechanical properties of talus deposits.Results indicate that the reconstructed meso-structures of talus deposits are more consistent with the actual situation because the self-adaptive PCNN digital image processing has a higher discrimination in the details of soil-rock segmentation.The existence and random distribution of rock blocks make the initial shear stiffness,the peak strength and the residual strength higher than those of the "pure soil" with particle size less than 1.25 cm apparently,but reduce the displacements required for the talus deposits reaching its peak shear strength.The increase of rock proportion causes a significant improvement in the internal friction angle of talus deposit,which to a certain degree leads to the characteristics of shear stress-displacement curves having a changing trend from the plastic strain softening deformation to the nonlinear strain hardening deformation,while an unconspicuous increase in cohesion.The uncertainty and heterogeneity of rock distributions cause the differences of rock proportion within shear zone,leading to a relatively strong fluctuation in peak strengths during the shear process,while movement features of rock blocks,such as translation,rotation and crossing,expand the scope of shear zone,increase the required shear force,and also directly lead to the misjudgment that the lower shear strength is obtained from the samples with high rock proportion.That,however,just explains the reason why the shear strength gained from a small amount of indoor test data is not consistent with engineering practice.展开更多
A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-effi...A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.展开更多
We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing f...We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing fast Fourier transform,inverse fast Fourier transform and the nonlinear leastsquare fitting on the diffraction pattern taken by a camera,the DIP method can quickly return an analytic expression,whose period is used to calculate widths of single slits.By comparing the measured results by the DIP method and the successional difference(SD)method,we find that for a single slit whose width is 60372μm,the DIP method is more accurate.Experimental results show that for single slits with widths between 40μm and 160μm,the relative error of the DIP method is less than 2.78%.Also,the DIP method can be used to measure the diameter of filament and fibres online in real time.展开更多
An improvement detecting method was proposed according to the disadvantages of testing method of optical axes parallelism of shipboard photoelectrical theodolite (short for theodolite) based on image processing. Point...An improvement detecting method was proposed according to the disadvantages of testing method of optical axes parallelism of shipboard photoelectrical theodolite (short for theodolite) based on image processing. Pointolite replaced 0.2'' collimator to reduce the errors of crosshair images processing and improve the quality of image. What’s more, the high quality images could help to optimize the image processing method and the testing accuracy. The errors between the trial results interpreted by software and the results tested in dock were less than 10'', which indicated the improve method had some actual application values.展开更多
In the present paper,a new image processing method for photocarrierspeckle fringe is proposed.A simple and fast filter is designed for different kinds of specklefringe with certain direction to eliminate the speckle e...In the present paper,a new image processing method for photocarrierspeckle fringe is proposed.A simple and fast filter is designed for different kinds of specklefringe with certain direction to eliminate the speckle effect.Fringe multiplication is carriedout with personal computer.The procedure of photocarrier speckle image collecting,pro-cessing,calculating and verifying is described with a practical example.展开更多
Asparagus officinalis L.is favored by its high health function,but its hybrid seeds are expensive.The amount of seed,seed plumpness and germination rate are related to the production costs of breeding enterprises and ...Asparagus officinalis L.is favored by its high health function,but its hybrid seeds are expensive.The amount of seed,seed plumpness and germination rate are related to the production costs of breeding enterprises and large growers.Therefore,it is necessary to investigate the seed number and thousand kernel weight of A.officinalis L.This study developed a quick and accurate method to measure the seed number and thousand kernel weight of A.officinalis L.using image processing technology.Seed sample of A.officinalis L.was scanned with 200 dpi resolution,and the seed number was then obtained using Image-ProPlus software.After weighing the seeds,thousand kernel weight was finally calculated.By recording‘macro’,the batch processing of the samples can also be realized.This method is simple and accurate,and can greatly save the time of investigation.展开更多
Global change affected by multiple factors,the consequences of which continue to be far-reaching,has the characteristics of large spatial scale and long-time scale.The demand for Earth observation technology has been ...Global change affected by multiple factors,the consequences of which continue to be far-reaching,has the characteristics of large spatial scale and long-time scale.The demand for Earth observation technology has been increasing for large-scale simultaneoiis observations and stable global observation over the long-term.A Moon-based observation platform,which uses sensors on the nearside lunar surface,is considered a reasonable solution.However,owing to a lack of appropriate processing methods for optical sensor data,global change study using this platform is not sufficient.This paper proposes two optical sensor imaging processing methods for the Moon-based platform:area imaging processing method(AIPM)and global imaging processing method(GIPM),primarily considering global change characteristics,optical sensor performance,and motion law of the Moon-based platform.First,the study proposes a simulation theory which includes the construction of a Moon-Sun elevation angle model and a global image mosaicking method.Then,coverage images of both image processing methods are simulated,and their features are quantitatively analyzed.Finally,potential applications are discussed.Results show that AEPM,whose coverage is mainly affected by lunar revolution,is approximately between 0%and 50%with a period of 29.5 days,which can help the study of large-scale instant change phenomena.GIPM,whose coverage is affected by Earth revolution,is conducive to the study of long term global-scale phenomena because of its sustained stable observation from 67°N-67°S on the Earth.AIPM and GIPM have great advantages in Earth observation of tripolar regions.The existence of top of the atmosphere(TOA)albedo balance line is verified from the GIPM perspective.These two imaging methods play a significant role in linking observations acquired from the Moon-based platform to Earth large-scale geoscience phenomena,and thus lay a foundation for using this platform to capture global environmental changes and new discoveries.展开更多
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.展开更多
The in-flight calibration and performance of the Solar Disk Imager(SDI),which is a pivotal instrument of the LyαSolar Telescope onboard the Advanced Space-based Solar Observatory mission,suggested a much lower spatia...The in-flight calibration and performance of the Solar Disk Imager(SDI),which is a pivotal instrument of the LyαSolar Telescope onboard the Advanced Space-based Solar Observatory mission,suggested a much lower spatial resolution than expected.In this paper,we developed the SDI point-spread function(PSF)and Image Bivariate Optimization Algorithm(SPIBOA)to improve the quality of SDI images.The bivariate optimization method smartly combines deep learning with optical system modeling.Despite the lack of information about the real image taken by SDI and the optical system function,this algorithm effectively estimates the PSF of the SDI imaging system directly from a large sample of observational data.We use the estimated PSF to conduct deconvolution correction to observed SDI images,and the resulting images show that the spatial resolution after correction has increased by a factor of more than three with respect to the observed ones.Meanwhile,our method also significantly reduces the inherent noise in the observed SDI images.The SPIBOA has now been successfully integrated into the routine SDI data processing,providing important support for the scientific studies based on the data.The development and application of SPIBOA also paves new ways to identify astronomical telescope systems and enhance observational image quality.Some essential factors and precautions in applying the SPIBOA method are also discussed.展开更多
In the task of classifying massive celestial data,the accurate classification of galaxies,stars,and quasars usually relies on spectral labels.However,spectral data account for only a small fraction of all astronomical...In the task of classifying massive celestial data,the accurate classification of galaxies,stars,and quasars usually relies on spectral labels.However,spectral data account for only a small fraction of all astronomical observation data,and the target source classification information in vast photometric data has not been accurately measured.To address this,we propose a novel deep learning-based algorithm,YL8C4Net,for the automatic detection and classification of target sources in photometric images.This algorithm combines the YOLOv8 detection network with the Conv4Net classification network.Additionally,we propose a novel magnitude-based labeling method for target source annotation.In the performance evaluation,the YOLOv8 achieves impressive performance with average precision scores of 0.824 for AP@0.5 and 0.795 for AP@0.5:0.95.Meanwhile,the constructed Conv4Net attains an accuracy of 0.8895.Overall,YL8C4Net offers the advantages of fewer parameters,faster processing speed,and higher classification accuracy,making it particularly suitable for large-scale data processing tasks.Furthermore,we employed the YL8C4Net model to conduct target source detection and classification on photometric images from 20 sky regions in SDSS-DR17.As a result,a catalog containing about 9.39 million target source classification results has been preliminarily constructed,thereby providing valuable reference data for astronomical research.展开更多
The China Space Station Telescope(CSST)is a 2 m three-mirror anastigmat equipped with a Fast Steering Mirror(FSM),which is part of its precision image stabilization system.The FSM is used to compensate for residuals f...The China Space Station Telescope(CSST)is a 2 m three-mirror anastigmat equipped with a Fast Steering Mirror(FSM),which is part of its precision image stabilization system.The FSM is used to compensate for residuals from the previous stage of the image stabilization system.However,a new type of image stabilization residual caused by image rotation and projection distortion is introduced when the FSM performs tip-tilt adjustments,reducing both the image stabilization accuracy and the absolute pointing accuracy of the CSST.In this paper,we propose a scheme to compute the image stabilization residuals across the full field of view(FOV)by using a reference star as the target for stabilization control,which can be utilized for subsequent image position correction.To achieve this,we developed a linear optical model for image point displacement by simplifying an existing image point displacement model and incorporating more readily available parameters.The computational accuracy of the new model is equivalent to that of the original,with computational differences of less than 0.03μm.Based on this linear model,we established a calculation model for image stabilization residuals,including those due to image rotation and projection distortion caused by FSM tip-tilt adjustments.This model provides a theoretical foundation for quantifying such residuals during the image stabilization process.Finally,the results of testing using this scheme are provided.Experimental results demonstrate that within the observation FOV of the CSST,when the FSM tilts by(1″,1″),the maximum absolute value of the image stabilization residuals accounts for 20%of the total image stabilization accuracy requirement.This finding underscores the necessity of computing and correcting these residuals to meet performance requirements.展开更多
Against the backdrop of massive sky survey data,the automated detection,classification,and parameter computation of targets have emerged as critical areas demanding urgent breakthroughs.However,in detection and classi...Against the backdrop of massive sky survey data,the automated detection,classification,and parameter computation of targets have emerged as critical areas demanding urgent breakthroughs.However,in detection and classification tasks,model accuracy is often constrained by issues such as small target sizes and insufficient feature information.To address this challenge,we innovatively constructs a fully automated astronomical image analysis pipeline that combines point source detection and classification,galaxy morphological classification,and parameter computation,forming an end-to-end solution.This pipeline achieves automated detection and morphological classification of both point sources and extended sources,and it is also able to compute the basic parameters of galaxy targets.The pipeline first accomplishes the detection and localization of target sources using the YOLOv9 model,and then leverages the optimized ResNet-AE model to initially categorize the detected targets into three major classes:stars,quasars,and galaxies.To tackle the problem of small sizes in some galaxy targets,we filtered out samples with larger sizes and distinct contours.Drawing on morphological characteristics,these samples were further classified into six categories via the DenseNet-SE4 model:barred spiral galaxies,cigar galaxies,elliptical galaxies,intermediate galaxies,spiral galaxies,and irregular galaxies.Following this classification,parameter computation was conducted on the targets.Experimental results show that the detection model has achieved better performance than previous studies,with a mean average precision of 85.20%at Intersection over Union values ranging from 0.5 to 0.95.Both classification models also reached an accuracy of over 85%on the test set.Compared with classical CNN networks,these two classification models boast higher precision,and the computation of target parameters has also yielded reliable outcomes.Experiments verify that this pipeline can act as a supplementary tool for astronomical image processing and be applied to data mining and analysis work in sky surveys.展开更多
A color visualization-based image processing method is developed in this paper to quantify the concentration evolution of the Brilliant Blue FCF transport through a two-dimensional homogeneous porous medium. A series ...A color visualization-based image processing method is developed in this paper to quantify the concentration evolution of the Brilliant Blue FCF transport through a two-dimensional homogeneous porous medium. A series of images are recorded at known time intervals, then the spatial distribution is estimated using a calibration curve, linking the gray pixel value to the solute concentration. Using a multi-dimensional concentration distribution map extraction technique the longitudinal and transverse concentration distributions could be observed with the physical model. The image-processed concentrations are then compared directly with the measured concentrations sampled at the outlet end. The tracer breakthrough curves sampled at multiple points along the central line of the medium are also compared with the solutions from the standard advection–dispersion equation model. It is shown that the non-invasive image processing method may be used to map the spatiotemporal evolution of a solute＇s concentration without disturbing the flow or the transport dynamics, although the measured solute breakthrough curves feature some non-Fickian dynamics that cannot be efficiently captured by the standard transport model.展开更多
A new method based on gray-natural logarithm ratio bilateral filtering is presented for image smoothing in this work. A new gray-natural logarithm ratio range filter kernel, leading to adaptive magnitude from image gr...A new method based on gray-natural logarithm ratio bilateral filtering is presented for image smoothing in this work. A new gray-natural logarithm ratio range filter kernel, leading to adaptive magnitude from image gray distinction information, is pointed out for the bilateral filtering. The new method can not only well restrain noise but also keep much more weak edges and details of an image, and preserve the original color transition of color images. Experimental results show the effectiveness for image denoising with our method.展开更多
This paper describes the preliminary study results of developing a hypervelocity terminal intercept guidance system of a multiple kinetic-energy impactor vehicle(MKIV).The proposed MKIV system is intended to fragment ...This paper describes the preliminary study results of developing a hypervelocity terminal intercept guidance system of a multiple kinetic-energy impactor vehicle(MKIV).The proposed MKIV system is intended to fragment or pulverize an asteroid of smaller than approximately 150 m in diameter that is detected with a mission lead time of shorter than 10 years,without using nuclear explosive devices.This paper focuses on the development of a new image processing algorithm based on Otsu’s method for the coordinated terminal intercept guidance and control of multiple kinetic-energy impactors employing visual and/or infrared sensors.A scaled polyhedron shape model of asteroid(216)Kleopatra is used as a fictional target asteroid.GPU-based simulation results demonstrate the feasibility of impacting a small irregular-shaped asteroid by using the proposed new image processing algorithm and a classical pulsed TPN(true proportional navigation)terminal guidance law.展开更多
Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometri...Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.展开更多
In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often distur...In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often disturb the image quality. A dedicated fitting correction method for high-resolution micro-CT is presented. The method converts each elementary X-ray response curve to an average one, and eliminates response inconsistency among pixels. Other factors of the method are discussed, such as the correction factor variability by different sampling frames and nonlinear factors over the whole spectrum. Results show that the noise and artifacts are both reduced in reconstructed images展开更多
Image captioning has seen significant research efforts over the last decade.The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate.Man...Image captioning has seen significant research efforts over the last decade.The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate.Many real-world applications rely on image captioning,such as helping people with visual impairments to see their surroundings.To formulate a coherent and relevant textual description,computer vision techniques are utilized to comprehend the visual content within an image,followed by natural language processing methods.Numerous approaches and models have been developed to deal with this multifaceted problem.Several models prove to be stateof-the-art solutions in this field.This work offers an exclusive perspective emphasizing the most critical strategies and techniques for enhancing image caption generation.Rather than reviewing all previous image captioning work,we analyze various techniques that significantly improve image caption generation and achieve significant performance improvements,including encompassing image captioning with visual attention methods,exploring semantic information types in captions,and employing multi-caption generation techniques.Further,advancements such as neural architecture search,few-shot learning,multi-phase learning,and cross-modal embedding within image caption networks are examined for their transformative effects.The comprehensive quantitative analysis conducted in this study identifies cutting-edgemethodologies and sheds light on their profound impact,driving forward the forefront of image captioning technology.展开更多
基金supported by the National Key R&D Program of China(2017YFF0205600)the International Research Cooperation Seed Fund of Beijing University of Technology(2018A08)+1 种基金Science and Technology Project of Beijing Municipal Commission of Transport(2018-kjc-01-213)the Construction of Service Capability of Scientific and Technological Innovation-Municipal Level of Fundamental Research Funds(Scientific Research Categories)of Beijing City(PXM2019_014204_500032).
文摘In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.
基金This research was supported by the Department of Mining Engineering at the University of Utah.In addition,the lead author wishes to acknowledge the financial support received from the Talent Introduction Project,part of the Elite Program of Shandong University of Science and Technology(No.0104060540171).
文摘This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(XRD)-based DIP method effectively analyzed the mineral composition contents and spatial distributions of granite. During the particle flow code(PFC2D) model calibration phase, the numerical simulation exhibited that the uniaxial compressive strength(UCS) value, elastic modulus(E), and failure pattern of the granite specimen in the UCS test were comparable to the experiment. By establishing 351 sets of numerical models and exploring the impacts of mineral composition on the mechanical properties of granite, it indicated that there was no negative correlation between quartz and feldspar for UCS, tensile strength(σ_(t)), and E. In contrast, mica had a significant negative correlation for UCS, σ_(t), and E. The presence of quartz increased the brittleness of granite, whereas the presence of mica and feldspar increased its ductility in UCS and direct tensile strength(DTS) tests. Varying contents of major mineral compositions in granite showed minor influence on the number of cracks in both UCS and DTS tests.
基金Project(2013BAB06B00) supported by the National Key Technology R&D Programof ChinaProject(2011CB013504) supported by the National Basic Research Program of ChinaProject(50911130366) supported by the National Natural Science Foundation of China
文摘The macro mechanical properties of materials with characteristics of large scale and complicated structural composition can be analyzed through its reconstructed meso-structures.In this work,the meso-structures of talus deposits that widely exist in the hydro-power engineering in the southwest of China were first reconstructed by small particles according to the in-situ photographs based on the self-adaptive PCNN digital image processing,and then numerical direct shear tests were carried out for studying the mechanical properties of talus deposits.Results indicate that the reconstructed meso-structures of talus deposits are more consistent with the actual situation because the self-adaptive PCNN digital image processing has a higher discrimination in the details of soil-rock segmentation.The existence and random distribution of rock blocks make the initial shear stiffness,the peak strength and the residual strength higher than those of the "pure soil" with particle size less than 1.25 cm apparently,but reduce the displacements required for the talus deposits reaching its peak shear strength.The increase of rock proportion causes a significant improvement in the internal friction angle of talus deposit,which to a certain degree leads to the characteristics of shear stress-displacement curves having a changing trend from the plastic strain softening deformation to the nonlinear strain hardening deformation,while an unconspicuous increase in cohesion.The uncertainty and heterogeneity of rock distributions cause the differences of rock proportion within shear zone,leading to a relatively strong fluctuation in peak strengths during the shear process,while movement features of rock blocks,such as translation,rotation and crossing,expand the scope of shear zone,increase the required shear force,and also directly lead to the misjudgment that the lower shear strength is obtained from the samples with high rock proportion.That,however,just explains the reason why the shear strength gained from a small amount of indoor test data is not consistent with engineering practice.
基金funded by the National Natural Science Foundation of China(41971226,41871357)the Major Research and Development and Achievement Transformation Projects of Qinghai,China(2022-QY-224)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA28110502,XDA19030303).
文摘A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.
基金National Natural Science Foundtion of China(No.11435011)Young Teachers Fund of Nanjing Institute of Technology,China(Nos.QKJ201907 and QKJ201908)+2 种基金China Scholarship Council(No.201708320319)Postgraduate Research and Practice Innovation Program of Jiangsu Province,China(No.KYZZ16-0349)Qing Lan Project of Jiangsu Province,China。
文摘We present an improved digital image processing(DIP)method to calculate the widths of single slits.Different from the traditional laser Fraunhofer diffraction experiment in college physical experiments,by performing fast Fourier transform,inverse fast Fourier transform and the nonlinear leastsquare fitting on the diffraction pattern taken by a camera,the DIP method can quickly return an analytic expression,whose period is used to calculate widths of single slits.By comparing the measured results by the DIP method and the successional difference(SD)method,we find that for a single slit whose width is 60372μm,the DIP method is more accurate.Experimental results show that for single slits with widths between 40μm and 160μm,the relative error of the DIP method is less than 2.78%.Also,the DIP method can be used to measure the diameter of filament and fibres online in real time.
文摘An improvement detecting method was proposed according to the disadvantages of testing method of optical axes parallelism of shipboard photoelectrical theodolite (short for theodolite) based on image processing. Pointolite replaced 0.2'' collimator to reduce the errors of crosshair images processing and improve the quality of image. What’s more, the high quality images could help to optimize the image processing method and the testing accuracy. The errors between the trial results interpreted by software and the results tested in dock were less than 10'', which indicated the improve method had some actual application values.
文摘In the present paper,a new image processing method for photocarrierspeckle fringe is proposed.A simple and fast filter is designed for different kinds of specklefringe with certain direction to eliminate the speckle effect.Fringe multiplication is carriedout with personal computer.The procedure of photocarrier speckle image collecting,pro-cessing,calculating and verifying is described with a practical example.
基金Modern Agricultural Industry Technology System Project(CARS-23-G-05)Modern Agricultural Science and Technology Innovation Project of Hebei Academy of Agriculture and Forestry Sciences(2019-3-2-1)the Third Batch of"Giant Plan"Vegetable Scientific Research and Innovation Team Project in Hebei Province.
文摘Asparagus officinalis L.is favored by its high health function,but its hybrid seeds are expensive.The amount of seed,seed plumpness and germination rate are related to the production costs of breeding enterprises and large growers.Therefore,it is necessary to investigate the seed number and thousand kernel weight of A.officinalis L.This study developed a quick and accurate method to measure the seed number and thousand kernel weight of A.officinalis L.using image processing technology.Seed sample of A.officinalis L.was scanned with 200 dpi resolution,and the seed number was then obtained using Image-ProPlus software.After weighing the seeds,thousand kernel weight was finally calculated.By recording‘macro’,the batch processing of the samples can also be realized.This method is simple and accurate,and can greatly save the time of investigation.
基金This research was supported by the National Natural Science Foundation of China(Grant No.41590853)and the Key Research Program of Frontier Sciences of Chinese Academy of Sciences(Grant No.QYZDY-SSW-DQC026).We also thanks NASA Jet Propulsion Laboratory for providing the free ephemeris data.
文摘Global change affected by multiple factors,the consequences of which continue to be far-reaching,has the characteristics of large spatial scale and long-time scale.The demand for Earth observation technology has been increasing for large-scale simultaneoiis observations and stable global observation over the long-term.A Moon-based observation platform,which uses sensors on the nearside lunar surface,is considered a reasonable solution.However,owing to a lack of appropriate processing methods for optical sensor data,global change study using this platform is not sufficient.This paper proposes two optical sensor imaging processing methods for the Moon-based platform:area imaging processing method(AIPM)and global imaging processing method(GIPM),primarily considering global change characteristics,optical sensor performance,and motion law of the Moon-based platform.First,the study proposes a simulation theory which includes the construction of a Moon-Sun elevation angle model and a global image mosaicking method.Then,coverage images of both image processing methods are simulated,and their features are quantitatively analyzed.Finally,potential applications are discussed.Results show that AEPM,whose coverage is mainly affected by lunar revolution,is approximately between 0%and 50%with a period of 29.5 days,which can help the study of large-scale instant change phenomena.GIPM,whose coverage is affected by Earth revolution,is conducive to the study of long term global-scale phenomena because of its sustained stable observation from 67°N-67°S on the Earth.AIPM and GIPM have great advantages in Earth observation of tripolar regions.The existence of top of the atmosphere(TOA)albedo balance line is verified from the GIPM perspective.These two imaging methods play a significant role in linking observations acquired from the Moon-based platform to Earth large-scale geoscience phenomena,and thus lay a foundation for using this platform to capture global environmental changes and new discoveries.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.12233012,the Strategic Priority Research Program of the Chinese Academy of Sciences,grant No.XDB0560102the National Key R&D Program of China 2022YFF0503003(2022YFF0503000)。
文摘The in-flight calibration and performance of the Solar Disk Imager(SDI),which is a pivotal instrument of the LyαSolar Telescope onboard the Advanced Space-based Solar Observatory mission,suggested a much lower spatial resolution than expected.In this paper,we developed the SDI point-spread function(PSF)and Image Bivariate Optimization Algorithm(SPIBOA)to improve the quality of SDI images.The bivariate optimization method smartly combines deep learning with optical system modeling.Despite the lack of information about the real image taken by SDI and the optical system function,this algorithm effectively estimates the PSF of the SDI imaging system directly from a large sample of observational data.We use the estimated PSF to conduct deconvolution correction to observed SDI images,and the resulting images show that the spatial resolution after correction has increased by a factor of more than three with respect to the observed ones.Meanwhile,our method also significantly reduces the inherent noise in the observed SDI images.The SPIBOA has now been successfully integrated into the routine SDI data processing,providing important support for the scientific studies based on the data.The development and application of SPIBOA also paves new ways to identify astronomical telescope systems and enhance observational image quality.Some essential factors and precautions in applying the SPIBOA method are also discussed.
基金supported by the National Natural Science Foundation of China (NSFC, Grant No. U1731128)
文摘In the task of classifying massive celestial data,the accurate classification of galaxies,stars,and quasars usually relies on spectral labels.However,spectral data account for only a small fraction of all astronomical observation data,and the target source classification information in vast photometric data has not been accurately measured.To address this,we propose a novel deep learning-based algorithm,YL8C4Net,for the automatic detection and classification of target sources in photometric images.This algorithm combines the YOLOv8 detection network with the Conv4Net classification network.Additionally,we propose a novel magnitude-based labeling method for target source annotation.In the performance evaluation,the YOLOv8 achieves impressive performance with average precision scores of 0.824 for AP@0.5 and 0.795 for AP@0.5:0.95.Meanwhile,the constructed Conv4Net attains an accuracy of 0.8895.Overall,YL8C4Net offers the advantages of fewer parameters,faster processing speed,and higher classification accuracy,making it particularly suitable for large-scale data processing tasks.Furthermore,we employed the YL8C4Net model to conduct target source detection and classification on photometric images from 20 sky regions in SDSS-DR17.As a result,a catalog containing about 9.39 million target source classification results has been preliminarily constructed,thereby providing valuable reference data for astronomical research.
基金financially supported by the National Key R&D Program of China(2022YFB3806300)。
文摘The China Space Station Telescope(CSST)is a 2 m three-mirror anastigmat equipped with a Fast Steering Mirror(FSM),which is part of its precision image stabilization system.The FSM is used to compensate for residuals from the previous stage of the image stabilization system.However,a new type of image stabilization residual caused by image rotation and projection distortion is introduced when the FSM performs tip-tilt adjustments,reducing both the image stabilization accuracy and the absolute pointing accuracy of the CSST.In this paper,we propose a scheme to compute the image stabilization residuals across the full field of view(FOV)by using a reference star as the target for stabilization control,which can be utilized for subsequent image position correction.To achieve this,we developed a linear optical model for image point displacement by simplifying an existing image point displacement model and incorporating more readily available parameters.The computational accuracy of the new model is equivalent to that of the original,with computational differences of less than 0.03μm.Based on this linear model,we established a calculation model for image stabilization residuals,including those due to image rotation and projection distortion caused by FSM tip-tilt adjustments.This model provides a theoretical foundation for quantifying such residuals during the image stabilization process.Finally,the results of testing using this scheme are provided.Experimental results demonstrate that within the observation FOV of the CSST,when the FSM tilts by(1″,1″),the maximum absolute value of the image stabilization residuals accounts for 20%of the total image stabilization accuracy requirement.This finding underscores the necessity of computing and correcting these residuals to meet performance requirements.
基金supported by the National Natural Science Foundation of China(NSFC,grant No.U1731128)。
文摘Against the backdrop of massive sky survey data,the automated detection,classification,and parameter computation of targets have emerged as critical areas demanding urgent breakthroughs.However,in detection and classification tasks,model accuracy is often constrained by issues such as small target sizes and insufficient feature information.To address this challenge,we innovatively constructs a fully automated astronomical image analysis pipeline that combines point source detection and classification,galaxy morphological classification,and parameter computation,forming an end-to-end solution.This pipeline achieves automated detection and morphological classification of both point sources and extended sources,and it is also able to compute the basic parameters of galaxy targets.The pipeline first accomplishes the detection and localization of target sources using the YOLOv9 model,and then leverages the optimized ResNet-AE model to initially categorize the detected targets into three major classes:stars,quasars,and galaxies.To tackle the problem of small sizes in some galaxy targets,we filtered out samples with larger sizes and distinct contours.Drawing on morphological characteristics,these samples were further classified into six categories via the DenseNet-SE4 model:barred spiral galaxies,cigar galaxies,elliptical galaxies,intermediate galaxies,spiral galaxies,and irregular galaxies.Following this classification,parameter computation was conducted on the targets.Experimental results show that the detection model has achieved better performance than previous studies,with a mean average precision of 85.20%at Intersection over Union values ranging from 0.5 to 0.95.Both classification models also reached an accuracy of over 85%on the test set.Compared with classical CNN networks,these two classification models boast higher precision,and the computation of target parameters has also yielded reliable outcomes.Experiments verify that this pipeline can act as a supplementary tool for astronomical image processing and be applied to data mining and analysis work in sky surveys.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.41772250,41602256)
文摘A color visualization-based image processing method is developed in this paper to quantify the concentration evolution of the Brilliant Blue FCF transport through a two-dimensional homogeneous porous medium. A series of images are recorded at known time intervals, then the spatial distribution is estimated using a calibration curve, linking the gray pixel value to the solute concentration. Using a multi-dimensional concentration distribution map extraction technique the longitudinal and transverse concentration distributions could be observed with the physical model. The image-processed concentrations are then compared directly with the measured concentrations sampled at the outlet end. The tracer breakthrough curves sampled at multiple points along the central line of the medium are also compared with the solutions from the standard advection–dispersion equation model. It is shown that the non-invasive image processing method may be used to map the spatiotemporal evolution of a solute＇s concentration without disturbing the flow or the transport dynamics, although the measured solute breakthrough curves feature some non-Fickian dynamics that cannot be efficiently captured by the standard transport model.
基金the National Natural Science Foundation of China under Grant No.60778046.
文摘A new method based on gray-natural logarithm ratio bilateral filtering is presented for image smoothing in this work. A new gray-natural logarithm ratio range filter kernel, leading to adaptive magnitude from image gray distinction information, is pointed out for the bilateral filtering. The new method can not only well restrain noise but also keep much more weak edges and details of an image, and preserve the original color transition of color images. Experimental results show the effectiveness for image denoising with our method.
文摘This paper describes the preliminary study results of developing a hypervelocity terminal intercept guidance system of a multiple kinetic-energy impactor vehicle(MKIV).The proposed MKIV system is intended to fragment or pulverize an asteroid of smaller than approximately 150 m in diameter that is detected with a mission lead time of shorter than 10 years,without using nuclear explosive devices.This paper focuses on the development of a new image processing algorithm based on Otsu’s method for the coordinated terminal intercept guidance and control of multiple kinetic-energy impactors employing visual and/or infrared sensors.A scaled polyhedron shape model of asteroid(216)Kleopatra is used as a fictional target asteroid.GPU-based simulation results demonstrate the feasibility of impacting a small irregular-shaped asteroid by using the proposed new image processing algorithm and a classical pulsed TPN(true proportional navigation)terminal guidance law.
基金funded by the National Natural Science Foundation of China(NSFC,Nos.12373086 and 12303082)CAS“Light of West China”Program+2 种基金Yunnan Revitalization Talent Support Program in Yunnan ProvinceNational Key R&D Program of ChinaGravitational Wave Detection Project No.2022YFC2203800。
文摘Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.
基金Supported by the National Basic Research Program of China ("973"Program)(2006CB601201)~~
文摘In high-resolution cone-beam computed tomography （CBCT） using the flat-panel detector, imperfect or defect detector elements cause ring artifacts due to the none-uniformity of their X-ray response. They often disturb the image quality. A dedicated fitting correction method for high-resolution micro-CT is presented. The method converts each elementary X-ray response curve to an average one, and eliminates response inconsistency among pixels. Other factors of the method are discussed, such as the correction factor variability by different sampling frames and nonlinear factors over the whole spectrum. Results show that the noise and artifacts are both reduced in reconstructed images
基金supported by the National Natural Science Foundation of China(Nos.U22A2034,62177047)High Caliber Foreign Experts Introduction Plan funded by MOST,and Central South University Research Programme of Advanced Interdisciplinary Studies(No.2023QYJC020).
文摘Image captioning has seen significant research efforts over the last decade.The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate.Many real-world applications rely on image captioning,such as helping people with visual impairments to see their surroundings.To formulate a coherent and relevant textual description,computer vision techniques are utilized to comprehend the visual content within an image,followed by natural language processing methods.Numerous approaches and models have been developed to deal with this multifaceted problem.Several models prove to be stateof-the-art solutions in this field.This work offers an exclusive perspective emphasizing the most critical strategies and techniques for enhancing image caption generation.Rather than reviewing all previous image captioning work,we analyze various techniques that significantly improve image caption generation and achieve significant performance improvements,including encompassing image captioning with visual attention methods,exploring semantic information types in captions,and employing multi-caption generation techniques.Further,advancements such as neural architecture search,few-shot learning,multi-phase learning,and cross-modal embedding within image caption networks are examined for their transformative effects.The comprehensive quantitative analysis conducted in this study identifies cutting-edgemethodologies and sheds light on their profound impact,driving forward the forefront of image captioning technology.
