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检索条件"任意字段=16th Image Processing: Algorithms and Systems Symposium 2018"

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Real-time Low Vision Simulation in Mixed Reality

Real-time Low Vision Simulation in Mixed Reality

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International IEEE Conference on Signal-image Technologies and Internet-Based System

作者： Valeria Acevedo Philippe Colantoni Éric Dinet Alain Trémeau Université de Lyon Université Jean Monnet Laboratoire Hubert Curien UMR

Visual impairments are a global health issue with profound socioeconomic ramifications in both the developing and the developed world. there exist ongoing research projects, that aim to investigate the influence of light in the perception of low vision individuals. But as of today, there is neither clear knowledge nor extensive data regarding the influence of light in low vision situations. this research will address these issues by introducing a methodology and a system to simulate visual impairments. A pipeline based on eye anatomy coupled with real-time image processing algorithms allows to dynamically simulate low vision specific characteristics of selected impairments in mixed reality. An original new approach based on massively parallelized processing combined with an efficient modeling of eye refractive errors aims to improve the accuracy of the low vision simulation.

关键词： image processing Heuristic algorithms Visual impairment Pipelines Mixed reality Real-time systems

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Application of Particle image Velocimetry Method Based on Full Convolution Neural Network in Turbulence Field

Application of Particle Image Velocimetry Method Based on Fu...

引用

International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Zhicheng Xie Shuqiang Guo School of Computing Northeast Electric Power University Jilin China

ISBN: (数字)9798331505264

ISBN: (纸本)9798331505271

Exploring fluid flow phenomena has always been a hot topic in fluid mechanics research. Particle image Velocimetry (PIV) is a non-contact technique applied in fluid mechanics laboratories for measuring the velocity field of fluids. the core of PIV lies in extracting displacement vector information from particle image pairs to ultimately generate a two-dimensional velocity field. Traditional methods typically estimate the two-dimensional velocity field using cross-correlation algorithms and optical flow techniques. In recent years, with the rapid development of artificial intelligence technologies and their high compatibility with PIV in image processing, there is significant potential and research value in designing deep learning techniques for accurately estimating fluid velocity vector fields in particle image velocimetry. Compared to traditional methods, the PIV technique proposed in this paper, based on fully convolutional neural networks, not only maintains the accuracy of velocity field estimation but also significantly enhances resolution and computational efficiency. Experiments demonstrate that the proposed method exhibits higher accuracy and stronger generalization capabilities.

关键词： Deep learning Visualization Accuracy Sea measurements Vectors Real-time systems Computational efficiency Convolutional neural networks Velocity measurement Meteorology

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the image-Based Automatic Detection Method for Cutter Ring Edge Wear of Shield Machine 16th

The Image-Based Automatic Detection Method for Cutter Ring E...

引用

16th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW)

作者： Bo, Wen Li, Fengyuan Cai, Xiaofeng Zhang, Changyou Chinese Acad Sci Inst Software Lab Parallel Software & Computat Sci Beijing Peoples R China State Key Lab Shield Machine & Boring Technol Zhengzhou 450001 Peoples R China

ISBN: (纸本)9789811945465;9789811945458

In order to satisfy the intelligent requirements of industrial systems and assist in automatic recognition of cutter wear, this paper proposes an image-based automatic detectionmethod for cutter ring edge wear of shieldmachine. the paper mainly studies: (1) Preprocess the original cutter images, the pixel image is generated by graying and thresholding methods, using the gray characteristics to suppress background, it has only two gray values;(2) Based on DBSCAN clustering algorithm, the optimization of cutter ring edge clusters is realized, and the edge pixel clusters are retained;(3) An ring edge extraction method based on structural constraints is proposed, the internal pixels are removed by orthogonal bidirectional projection, we obtained the preliminary image edge extraction results;(4) the circular edge of cutter-image is obtained by remaining pixels polynomial fitting based on polar coordinates. Finally, through the reference the actual size of cutter, the actual radius error is less than 3%. the experimental results show that this method can automatically and accurately detect the actual cutter wear of shield machine, and it provides an effective solution for the intelligent detection of cutter wear.

关键词： image processing Shield machine Cutter ring edge Wear detection Automation

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Improving the criteria for quality assessment of image processing algorithms 16

Improving the criteria for quality assessment of image proce...

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16th International Conference on Electronic Devices and Control systems 2020, EDCS 2020

作者： Dubinin, D.V. Kochegurov, A.I. Geringer, V.E. Tomsk State University of Control Systems and Radioelectronics Lenin Avenue 40 Tomsk634050 Russia National Research Tomsk Polytechnic University Lenin Avenue 30 Tomsk634050 Russia Baden-Wuerttemberg Cooperative State University Faculty of Engineering Fallenbrunnen 2 FriedrichshafenD-88045 Germany

Quality criteria are the essence of a measurement system. the goal of assessing the quality of software elements (algorithms) used for image processing is to ensure control of technical performance indicators of the system as a whole or its individual functional units under the reduction of costs associated with minimizing the loss function (tuning and debugging). the correct choice of individual metrics for the generalized quality indicator to solve tasks in a particular subject area is one of the key steps in system optimization. It ensures the most flexible approach to testing the developed software elements, identifying and eliminating their functional shortcomings. At the same time, we can say that in this way the generalized indicator of the entire system (its goal function) is optimized. © Published under licence by IOP Publishing Ltd.

关键词： image enhancement

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A Fully-Automated Paper ECG Digitisation Algorithm for e-Health Applications

A Fully-Automated Paper ECG Digitisation Algorithm for e-Hea...

引用

International Conference on Wireless Communications and Signal processing (WCSP)

作者： Tao Wang Yiquan Wang Zhisen Chang Xiao Lyu Zhipei Huang Fei Qin University of Chinese Academy of Sciences Beijing China Beijing Alpha Yuan Technology Co. Ltd. Beijing China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

the electrocardiogram (ECG) is an important non-invasive tool for diagnosing heart and cardiovascular diseases. However, traditional ECG systems often provide images, which makes it challenging to directly utilize the image-based data in various applications that require 1-D signals. therefore, the digitalization of ECG reports is essential for the establishment of electronic medical archives, advanced diagnostic tools, and intelligent healthcare systems. Previous efforts to digitize paper-based ECGs have been limited by the need to manually select regions of interest, limited accuracy in handling overlapping ECG leads, and lack of batch processing capabilities. We present a fully automated method for digitizing ECG reports that requires only a predefined lead distribution, eliminating the need for manual lead position selection. this method effectively addresses the challenge of overlapping leads and has the capability for automated batch processing. Validation against a subset of the PTB-XL dataset demonstrated high accuracy and reliability (Root Mean Square Error: 0.036 (mV), Pearson Correlation Coefficient: 0.977). To further verify the generalizability of the method, we applied the algorithm to hospital ECG reports. the results, evaluated by expert cardiologists, confirmed that our method produced consistently high-quality digitalization and demonstrated its applicability to different types of ECG reports.

关键词： Wireless communication Accuracy Hospitals Signal processing algorithms Batch production systems Electrocardiography Robustness Root mean square Standards Signal resolution

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An image Encryption Algorithm Suitable for Medical images

An Image Encryption Algorithm Suitable for Medical Images

引用

IEEE International Scientific Conference on Informatics

作者： Jakub Oravec Ľuboš Ovseník Maroš Lapčák Norbert Zdravecký Samuel Andrejčík Dept. of Electronics and Multimedia Communications FEEI Technical University of Košice Košice Slovakia

Security of data becomes more and more important each day. the importance is even more pronounced if the data contain sensitive information, such as those shown in medical images. there are already several solutions that can be used in order to protect medical images during their storage or transmission. the most popular of those is probably encryption by conventional encryption algorithms such as Advanced Encryption Standard. this proposal tries to investigate possibility of using dedicated image encryption algorithms that have applications in fields of steganography and biometric systems for encryption of medical images. the dedicated image encryption algorithms can be easily adjusted for processing medical images, what can be verified by several experiments. Main advantage of this proposal lies in an addition of a substitution block, which should increase the security of whole algorithm. the performance of our solution will be evaluated by several numerical parameters and those will be compared with results reported in similar works.

关键词： Steganography Microcomputers Real-time systems Encryption Proposals Informatics Smart devices

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Normalized Convolution Upsampling for Refined Optical Flow Estimation 16

Normalized Convolution Upsampling for Refined Optical Flow E...

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16th International Joint Conference on Computer Vision, Imaging and Computer Graphics theory and Applications (VISIGRAPP) / 16th International Conference on Computer Vision theory and Applications (VISAPP)

作者： Eldesokey, Abdelrahman Felsberg, Michael Linkoping Univ Comp Vis Lab Linkoping Sweden

ISBN: (纸本)9789897584886

Optical flow is a regression task where convolutional neural networks (CNNs) have led to major breakthroughs. However, this comes at major computational demands due to the use of cost-volumes and pyramidal representations. this was mitigated by producing flow predictions at quarter the resolution, which are upsampled using bilinear interpolation during test time. Consequently, fine details are usually lost and post-processing is needed to restore them. We propose the Normalized Convolution UPsampler (NCUP), an efficient joint upsampling approach to produce the full-resolution flow during the training of optical flow CNNs. Our proposed approach formulates the upsampling task as a sparse problem and employs the normalized convolutional neural networks to solve it. We evaluate our upsampler against existing joint upsampling approaches when trained end-to-end with a a coarse-to-fine optical flow CNN (PWCNet) and we show that it outperforms all other approaches on the FlyingChairs dataset while having at least one order fewer parameters. Moreover, we test our upsampler with a recurrent optical flow CNN (RAFT) and we achieve state-of-the-art results on Sintel benchmark with similar to 6% error reduction, and on-par on the KITTI dataset, while having 7.5% fewer parameters (see Figure 1). Finally, our upsampler shows better generalization capabilities than RAFT when trained and evaluated on different datasets.

关键词： Optical Flow Estimation CNNs Joint image Upsampling Normalized Convolution Spare CNNS

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Early Defect Detection in Conveyor Belts using Machine Vision 16

Early Defect Detection in Conveyor Belts using Machine Visio...

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作者： Netto, Guilherme G. Coelho, Bruno N. Delabrida, Saul E. Sinatora, Amilton Azpurua, Hector Pessin, Gustavo Oliveira, Ricardo A. R. Bianchi, Andrea G. C. Fed Univ Ouro Preto UFOP Sch Mines Dept Engn Control & Automat 122 Diogo de Vasconcelos BR-35400000 Ouro Preto MG Brazil Fed Univ Ouro Preto UFOP Comp Dept 122 Diogo de Vasconcelos BR-35400000 Ouro Preto MG Brazil Vale Inst Technol ITV 31 Juscelino Kubitschek BR-35400000 Ouro Preto MG Brazil

ISBN: (纸本)9789897584886

Continuous belt monitoring is of utmost importance since wears on its surface can develop into tears and even rupture. It can causes the interruption of the conveyor, and consequently, loss of capital, or even worse, serious or fatal accidents. this paper proposes a laser-based machine vision method for detecting defects in conveyor belts to solve the monitoring problem. the approach transforms an image of a laser line into a one-dimensional signal, then analyzes it to detect defects, considering that variations in this signal are caused by defects/imperfections on the belt surface. Differently from previous works, the proposed method can identify a defect through a 2D reconstruction of it. the results reveal that the proposed method was capable to detect superficial imperfections in simulated conveyor belt experiments, achieving high values in metrics such as precision and recall.

关键词： image and Signal processing Curvature Outlier Defects Detection Machine Vision Inspection Maintenance

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Smart Cities Mobility Monitoring through Automatic License Plate Recognition and Vehicle Discrimination 16

Smart Cities Mobility Monitoring through Automatic License P...

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16th IEEE International symposium on Broadband Multimedia systems and Broadcasting (IEEE BMSB)

作者： Spanu, M. Bertolusso, M. Bingol, G. Serreli, L. Castangia, C. G. Anedda, M. Fadda, M. Farina, M. Giusto, D. D. Univ Cagliari Dept Elect & Elect Engn DIEE UdR CNIT Cagliari Italy Univ Sassari Sassari Italy

ISBN: (纸本)9781665449083

this work deals with vehicular monitoring within smart cities through Automatic License Plate Recognition (ALPR) techniques and vehicle discrimination object detection (YOLO), in order to obtain timely statistical data. the combined use of the two techniques allows to obtain much more refined data than a simple vehicle counter. Moreover, the collected data undergoes a process of anonymization in accordance with the European regulations for the protection of personal data (GDPR). the use of convolutional neural networks (CNN) made it possible to obtain vehicle tracking statistics, returning daily, weekly, monthly and yearly habits with the ultimate goal of allowing a monitoring and control of the city traffic conditions. the results obtained showed a high accuracy in the classification of vehicles and a wide range of statistics concerning the occurrences of each vehicle within the area of interest.

关键词： Automatic License Plate Detection image processing Smart City Vehicle Discrimination Deep Learning

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Video Enhancement Based on Unpaired Learning 16

Video Enhancement Based on Unpaired Learning

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16th IEEE International symposium on Broadband Multimedia systems and Broadcasting (IEEE BMSB)

作者： Chen, Jinjin Gan, Wenyao Zhang, Hengsheng Xie, Rong Song, Li Chen, Min Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China MIGU Co Ltd Beijing Peoples R China

ISBN: (纸本)9781665449083

Distortion of real video is affected by many factors. Many existing old videos n have the problem of low definition. However, most video enhancement based on paired learning is trained for specific degradation problem, lack of the ability to enhance real low-definition video with unknown distortion. In this paper, we propose a joint video enhancement algorithm based on unpaired learning, which uses a high-definition video to enhance a low-definition video with similar contents. In order to train the network, we also build three pairs of unpaired video datasets with chimpanzee, city night view and military figures as contents. In experiments, we compare our method with enhancement algorithm based on paired learning and other unpaired framework and find that our method achieves a higher performance,

关键词： Video enhancement Deep learning Unpaired learning

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