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image processing based three-dimensional model reconstruction for cross-platform numerical simulation

China Foundry 2023年第2期20卷 139-147页

作者： Yu-cheng Sun Yu-hang Huang Na Li Xiao Han Ai-long Jiang Jin-wu Kang Ji-wu Wang Hai-liang Yu State Key Laboratory of Engine Reliability Weichai Power Co.Ltd.Weifang 261061ShandongChina School of Mechanical Engineering Central South UniversityChangsha 41000China School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Key Laboratory for Advanced Materials processing Technology School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical *** a complex problem relating to multi-field,multi-process and multi-scale,different computing tools have to be developed so as to solve particular fields at different scales and for different ***,the integration of different types of software is ***,it is difficult to perform the transfer of the meshes and simulated results among software packages because of the lack of shared data formats or encrypted data *** image processing based method for three-dimensional model reconstruction for numerical simulation was proposed,which presents a solution to the integration problem by a series of slice or projection images obtained by the post-processing modules of the numerical simulation *** means of mapping image pixels to meshes of either finite difference or finite element models,the geometry contour can be extracted to export the stereolithography *** values of results,represented by color,can be deduced and assigned to the *** the models with data can be directly or indirectly integrated into other software as a continued or new numerical *** three-dimensional reconstruction method has been validated in numerical simulation of castings and case studies were provided in this study.

关键词： cross-platform numerical simulation 3D model reconstruction image processing slice

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image processing analysis to track colour changes on apple and correlate to moisture content in drying stages

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Food Quality and Safety 2018年第2期2卷 105-110页

作者： Ganesh C.Bora Rohit Pathak Mojtaba Ahmadi Purbasha Mistry Department of Agricultural and Biological Engineering Mississippi State UniversityMississippiUSA Department of Agricultural and Biosystems Engineering North Dakota State UniversityFargoNorth DakotaUSA

Colour and moisture content are two most important attributes of the commercial food *** of moisture content is very important to know the storability of the food *** also relates to the process of drying in a fruit or *** drying and shrinkage deteriorates the quality of food *** goal of the experiment was to examine the changes in RGB values of an apple during drying at different *** this study,emphasis was given on how the colour changes when there is a significant change in the moisture content of the *** randomly chosen varieties of apples were sliced to 8 mm thickness and dried in vacuum oven at 60°C,70°C,and 80°*** loss of moisture was recorded for every 30 min interval and corresponding digital images were taken to determine the change in RGB *** images that were captured during the study was analysed in MATLAB image analysis computer *** analysis of moisture content and average colour share with respect to time showed that average colour share value decreases with time at all three *** than 50 per cent of variation in moisture content was explained by average colour *** is a significant linear relationship between moisture content and colour changes in RGB and can be used to predict the moisture content of apple during drying process.

关键词： image processing colour moisture content apple drying temperature

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image processing methods to evaluate tomato and zucchini damage in post-harvest stages

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International Journal of Agricultural and Biological Engineering 2017年第5期10卷 126-133页

作者： José Antonio Alvarez-Bermejo Cynthia Giagnocavo Li Ming Encarnación Castillo Morales Diego P.Morales Santos Yang Xinting Department of Informatics CeiA3University of AlmeriaAlmeriaCP 04120Spain Cátedra(Chair)Coexphal-UAL of Horticulture Cooperative Studies and Sustainable DevelopmentUniversity of AlmeríaSpain Beijing Research Center for Information Technology in Agriculture/National Engineering Research Center for Information Technology in Agriculture/National Engineering Laboratory for Agri-product Quality Traceability/Key Laboratory for Information Technologies in Agriculture Ministry of AgricultureBeijing 100097China Department of Electronics and Computer Technology Facultad de CienciasGranadaCP 18071Spain

Through the supply chain,the quality or quality change of the products can generate important *** quality control in some steps is made manually that supposes a high level of subjectivity,controlling the quality and its evolution using automatic systems can suppose a reduction of the *** some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this *** steps in the supply chain are considered,the feeding of the raw products into the handling chain(because low quality generates a reduction of the chain productivity)and the cool storage of the processed products(as the value at the market is reduced).It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products(corresponding to specific farmers/suppliers,it should be asked to improve to maintain the productivity of the line).The second stage is analyzing the evolution of the products along the cool chain(storage and transport),the use of an App developed to be use under Android was proposed to substitute the“visual”evaluation used in *** algorithms used,including stages of pre-treatment,segmentation,analysis and presentation of the results take account of the short time available and the limited capacity of the *** performance techniques were applied to the homography stage to discard some of the images,resulting in better *** threads and renderscript kernels were created to parallelize the methods used on the resulting images being able to inspect faster the *** proposed method achieves success rates comparable to,and improving,the expert inspection.

关键词： image processing color space smartphone efficient stitching homography controlled supervision artificial vision embedded parallel processing injury assessment traceability post-harvest control feature detection

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image processing based real-time variable-rate chemical spraying system for disease control in paddy crop

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Artificial Intelligence in Agriculture 2020年第1期4卷 21-30页

作者： V.K.Tewari C.M.Pareek Gurdeep Lal L.K.Dhruw Naseeb Singh Agricultural and Food Engineering Department Indian Institute of Technology KharagpurWest Bengal 721302India Division of Agricultural Engineering ICAR Research Complex for NEH RegionUmiamMeghalaya 793103India

The agrochemical applicationwith conventional sprayers results inwastage of applied chemicals,which not only increases the economic losses but also pollutes the *** order to overcome these drawbacks,an image processing based real-time variable-rate chemical spraying systemwas developed for the precise application of agrochemicals in diseased paddy crop based on crop disease severity *** developed system comprised ofweb cameras for image acquisition,laptop for image processing,microcontroller for controlling the system functioning,and solenoid valve assisted spraying *** chromatic aberration(CA)based image segmentation method was used to detect the diseased region of paddy *** system further calculated the disease severity level of paddy plants,based onwhich the solenoid valves remained on for a specific timeduration so that the required amount of agrochemical could be sprayed on the diseased paddy *** performance of developed sprayer prototype was evaluated in the variable-rate application(VRA)and constant-rate application(CRA)*** field testing results showed a minimum 33.88%reduction in applied chemical while operating in the VRA mode as compared with the CRA ***,the developed systemappears promising and could be used extensively to reduce the cost of pest management as well as to control environmental pollution due to such agrochemicals.

关键词： Variable-rate chemical application Spraying image processing Microcontroller Plant disease severity

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image processing of ESPI based on measurement the welding dynamic displacement fields

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China Welding 2004年第2期13卷 111-114页

作者：陶军李冬青范成磊刘忠国 State Key Laboratory of Advanced Welding Production Technology Harbin Institute of Technology Harbin 150001

A dual-beam electronic speckle pattern interferometry (ESPI) system was adopted to get speckle patterns for the measurement of welding dynamic displacement fields. The mathematical model of this system was described, based on which methods of the ESPI pattern image processing were discussed. Gray transformation and histogram equalization were used to enhance the contrast of speckle patterns. A discrete cosine image processing method was carried out and an exponent low-pass filter was chosen to reduce multiplicative noise in speckle patterns. Speckle grain noise can be eliminated effectively after these processes.

关键词： welding electronic speckle pattern interferometry image processing discrete cosine low-pass exponent filter

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An image processing method for feature extraction and dynamic tracking of particle clusters in CFBs

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Particuology 2023年第6期77卷 1-13页

作者： Yue Guo Shangyi Yin Shibing Lu Tao Song Huijun Ge Ping Lu School of Energy and Mechanical Engineering Nanjing Normal UniversityNanjing210023China

A new image processing method based on the high-speed camera is proposed to identify,locate,and track *** instantaneous characteristic parameters of particle clusters in the riser of the circu-lating fluidized bed(CFB)can be acquired,such as solids holdup,vertical velocity,lateral displacement,aspect ratio and *** were carried out with glass bead particles,river sand particles and FCC *** time series of images of gas-solid flow in a CFB riser with a 100 mm x 25 mm cross-section and 3.2 m in length were obtained using high-speed *** k-means++clustering algorithm is utilized to identify the clusters,centroid is applied to locate the clusters,and the cross-correlation algorithm is employed to track the specific clusters and number them to get the instantaneous characteristic *** results illustrate that the shapes of clusters in the center area are closest to circle,moving upwards at a uniform speed,while the clusters in the side-wall area are mostly elongated or long chain-like,moving slowly *** the transition area,the clusters are more complex,moving upwards at a constant speed,and having large lateral *** results show that the image processing method used in this study is successful in acquiring the dynamic and structural parameters of the clusters simultaneously.

关键词： Circulating fluidized bed Clusters image processing Dynamic tracking

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Spatial resolution and image processing for pinhole camera-based X-ray fluorescence imaging: a simulation study

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Nuclear Science and Techniques 2022年第5期33卷 135-153页

作者： Ze He Ning Huang Peng Wang Zi-Han Chen Bo Peng Key Laboratory of Radiation Physics and Technology of the Ministry of Education Institute of Nuclear Science and TechnologySichuan UniversityChengdu 610064China

Spatial resolution and image-processing methods for full-field X-ray fluorescence(FF-XRF)imaging using X-ray pinhole cameras were studied using Geant4simulations with different geometries and algorithms for image *** main objectives were:(1)calculating the quantum efficiency curves of specific cameras,(2)studying the relationships between the spatial resolution and the pinhole diameter,magnification,and camera binning value,and(3)comparing image-processing methods for pinhole camera *** results were obtained using a point and plane source as the X-ray fluorescence emitter and an array of 100×100 silicon pixel detectors as the X-ray *** quantum efficiency of a back-illuminated deep depletion(BI-DD)structure was above 30%for the XRF energies in the 0.8–9 keV range,with the maximum of 93.7%at 4 *** best spatial resolution of the pinhole camera was 24.7μm and 31.3 lp/mm when measured using the profile function of the point source,with the diameter of 20μm,magnification of 3.16,and camera bin of 1.A blind deconvolution algorithm with Gaussian filtering performed better than the Wiener filter and Richardson iterative methods on FF-XRF images,with the signal-to-noise ratio of 7.81 dB and improved signalto-noise ratio of 7.24 dB at the diameter of 120μm,magnification of 1.0,and camera bin of 1.

关键词： Full-field X-ray fluorescence(FF-XRF) X-ray pinhole camera Spatial resolution image processing

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Detection of abnormal hydroponic lettuce leaves based on image processing and machine learning

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Information processing in Agriculture 2023年第1期10卷 1-10页

作者： Ruizhe Yang Zhenchao Wu Wentai Fang Hongliang Zhang Wenqi Wang Longsheng Fu Yaqoob Majeed Rui Li Yongjie Cui College of Mechanical and Electronic Engineering Northwest A&F UniversityYanglingShaanxi 712100China Xi’an Agriculture Machinery Management and Extension Station Xi’anShaanxi 710065China Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural AffairsYanglingShaanxi 712100China Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service YanglingShaanxi 712100China Faculty of Agricultural Engineering and Technology University of AgricultureFaisalabad 38000Pakistan Center for Precision and Automated Agricultural Systems Washington State UniversityProsserWA 99350USA Suide County Lanhuahua Ecological Food Co. Ltd.SuideShaanxi 718000China

Accurate and fast detection of abnormal hydroponic lettuce leaves is primary technology for robotic *** and rotten leaves are main types of abnormal leaves in hydroponic *** study aims to demonstrate a feasibility of detecting yellow and rotten leaves of hydroponic lettuce by machine learning models,*** Linear Regression(MLR),K-Nearest Neighbor(KNN),and Support Vector Machine(SVM).One-way analysis of variance was applied to reduce RGB,HSV,and L*a*b*features number of hydroponic lettuce *** binarization,image mask,and image filling methods were employed to segment hydroponic lettuce from an image for models *** showed that G,H,and a*were selected from RGB,HSV,and L*a*b*for training *** took about 20.25 s to detect an image with 30244032 pixels by KNN,which was much longer than MLR(0.61 s)and SVM(1.98 s).MLR got detection accuracies of 89.48%and 99.29%for yellow and rotten leaves,respectively,while SVM reached 98.33%and 97.91%,*** was more robust than MLR in detecting yellow and rotten leaves of ***,it was possible for abnormal hydroponic lettuce leaves detection by machine learning methods.

关键词： Hydroponic lettuce Machine learning image processing Abnormal leaves Automatic sorting

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HyperDB：A Hyperspectral Land Class Database Designed for an image processing System

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Tsinghua Science and Technology 2017年第1期22卷 112-118页

作者： Yizhou Fan Ding Ni Hongbing Ma Department of Electronic Engineering Tsinghua UniversityBeijing 100084 China

Hyperspectral remote sensing is becoming more and more important amongst remote sensing techniques. In this paper, we present a hyperspectral database（Hyper DB） designed to cooperate with an embedded hyperspectral image processing system developed by the authors. Hyperspectral data are recognized and categorized by their land coverage class and band information, and can be imported from various sources such as airborne and spaceborne sensors carried by airplanes or satellites, as well as handhold instruments based on in situ ground observations. Spectral library files can be easily stored, indexed, viewed, and exported. Since Hyper DB follows standard design principles—independence, data safety, and compatibility—it satisfies the practical demand for managing categorized hyperspectral data, and can be readily expanded to other peripheral applications.

关键词： hyperspectral database spectral library image processing

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Review-material degradation assessed by digital image processing:Fundamentals,progresses,and challenges

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Journal of Materials Science & Technology 2020年第18期52卷 146-162页

作者： Da-Hai Xia Shizhe Song Lei Tao Zhenbo Qin Zhong Wu Zhiming Gao Jihui Wang Wenbin Hu Yashar Behnamian Jing-Li Luo Tianjin Key Laboratory of Composite and Functional Materials Tianjin 300354China School of Materials Science and Engineering Tianjin UniversityTianjin 300354China CNOOC Tianjin Chemical Research&Design Institute Co.Ltd Tianjin 300131China Department of Chemical and Materials Engineering University of AlbertaEdmontonAlbertaT6G 1H9Canada

Material degradation is accompanied by the changes in surface structure,morphology,and *** changes can be recorded by a variety of image acquisition devices that export digital images in grayscale or true color to a *** regarding corrosion type and extent can be extracted with image processing *** paper provides a comprehensive review of material degradation assessed by digital image *** image processing systems used to assess material degradation are briefly reviewed,and the algorithms developed to process metallic materials degradation images are *** and electrochemical methods that can be used to support digital image processing results are summarized,and future work that will augment the present methods of evaluating material degradation are discussed.

关键词： image processing Material degradation Corrosion Pitting Fuzzy K-S entropy

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