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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VII"

共 12978 条记录，以下是4571-4580 订阅

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Computer Vision System for Defects Detection in PET Preform 21

Computer Vision System for Defects Detection in PET Preform

引用

21st International conference on Methods and Models in Automation and Robotics (MMAR)

作者： Laucka, Andrius Andriukaitis, Darius Valinevicius, Algimantas Navikas, Dangirutis Kaunas Univ Technol Dept Elect Engn LT-51368 Kaunas Lithuania

ISBN: (纸本)9781509018666

The computer vision systems are mainly devoted for production monitoring in quality inspection systems. It is the fastest growing and most popular non-invasive product defects detection method. The productivity of electronic components growth and their prices decline creates favorable conditions for the development of image processing systems for industrial production. The food industry is one of the main industries. Production volumes grow along with human population growth. Containers for food industry are made in very large quantities and demand on quality inspection system plays important role. An automated computer vision system was developed for the control of PET preparation quality. The implementation of the designed system was presented in this article. The system used for image processing algorithms to inspect the lateral and upper parts of the workpiece. The system is designed according to its operating parameters. Reached throughput is 10,000 workpieces per hour.

关键词： PET computer vision systems digital image processing electronic systems

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Automatic Thresholding Method for Edge Detection algorithms 8

Automatic Thresholding Method for Edge Detection Algorithms

引用

8th International conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Anghelescu, Petre Iliescu, Vlad Gabriel Mara, Constantin Gavriloaia, Mihai-Bogdan Univ Pitesti Dept Elect Commun & Comp Pitesti Romania Univ Politehn Bucuresti Telecommun Dpt Elect Bucharest Romania

ISBN: (纸本)9781509020478

This paper describes an efficient edge detection algorithm that can be used as a plug-in for digital image processing systems. The proposed algorithm uses a method based on iterative clustering targeting a reduced number of operations. The algorithm splits the image into two parts, background and foreground, and calculates the mean value for each of them. Based on these results, the new threshold value will be obtained and looped until the mean values remain unchanged. The only pixels affected by the change are the pixels with values between the previous two thresholds, so only they have to be redistributed to a new class. As a result, only few operations are needed in order to obtain the desired threshold. All the algorithms and results obtained in this paper are developed and tested using the C# programming language.

关键词： image processing edge detection thresholding algorithms non-maximum suppression cluster based methods

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Spatiotemporal hazard mapping of a flood event "migration" in a Transboundary River Basin as an operational tool in Flood Risk Management

Spatiotemporal hazard mapping of a flood event "migration" i...

引用

conference on Active and Passive Microwave Remote Sensing for Environmental Monitoring

作者： Perrou, Theodora Papastergios, Asterios Parcharidis, Issaak Chini, Marco Harokopio Univ Athens Dept Geog Athens 17671 Greece LIST 41 Rue Brill L-4422 Luxembourg Luxembourg

ISBN: (数字)9781510613171

ISBN: (纸本)9781510613171;9781510613164

Flood disaster is one of the heaviest disasters in the world. It is necessary to monitor and evaluate the flood disaster in order to mitigate the consequences. As floods do not recognize borders, transboundary flood risk management is imperative in shared river basins. Disaster management is highly dependent on early information and requires data from the whole river basin. Based on the hypothesis that the flood events over the same area with same magnitude have almost identical evolution, it is crucial to develop a repository database of historical flood events. This tool, in the case of extended transboundary river basins, could constitute an operational warning system for the downstream area. The utility of SAR images for flood mapping, was demonstrated by previous studies but the SAR systems in orbit were not characterized by high operational capacity. Copernicus system will fill this gap in operational service for risk management, especially during emergency phase. The operational capabilities have been significantly improved by newly available satellite constellation, such as the Sentinel-1A&B mission, which is able to provide systematic acquisitions with a very high temporal resolution in a wide swath coverage. The present study deals with the monitoring of a transboundary flood event in Evros basin. The objective of the study is to create the "migration story" of the flooded areas on the basis of the evolution in time for the event occurred from October 2014 till May 2015. Flood hazard maps will be created, using SAR-based semi-automatic algorithms and then through the synthesis of the related maps in a GIS-system, a spatiotemporal thematic map of the event will be produced. The thematic map combined with TanDEM-X DEM, 12m/pixel spatial resolution, will define the non-affected areas which is a very useful information for the emergency planning and emergency response phases. The Sentinels meet the main requirements to be an effective and suitable operational

关键词： Sentinel-1 SAR image processing Transboundary river basin Flood mapping TanDEM-X DEM Flood risk management Evros River

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A Survey of Blob Detection algorithms for Biomedical images 7

A Survey of Blob Detection Algorithms for Biomedical Images

引用

7th International conference on Information Communication Technology for Embedded systems (IC-ICTES)

作者： Han, Kay Thwe Min Uyyanonvara, Bunyarit Thammasat Univ Sirindhorn Int Inst Technol Sch Informat Comp & Commun Technol 131 Moo 5 Bangkadi 12000 Muang Pathumtha Thailand

ISBN: (纸本)9781509022489

This paper presents a survey of blob detection methods which has been applied on image processing with relation of medical images proposed by literature. "The blob detection is a mathematical method which detects regions or points in digital images". [1] The regions or points which have noticeable difference with their surroundings is called blob. Given the increased interest in biomedical image processing system, many algorithms and methods have been reported to apply but there is no systematic survey and classification of the blob detection for medical images and how they have been assessed and applied. The findings, which is the most usable methods of blob detectors in biomedical image processing has been presented. It was also investigated how these studies have been surveyed, how they evolved in the main digital libraries over the last decade, and what points deserves further attention, through new research. From this survey, practitioners and researchers can adopt the blob detection methods and analyze to use these methods in their research for further development.

关键词： Blob Detection Survey Medical image processing Blob Detection Methods

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Adaptive Multispectral GPU Accelerated Architecture for Earth Observation Satellites

Adaptive Multispectral GPU Accelerated Architecture for Eart...

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IEEE International conference on Imaging systems and Techniques (IST) / IEEE International School on Imaging

作者： Davidson, R. L. Bridges, C. P. Univ Surrey Surrey Space Ctr Guildford GU2 7XH Surrey England

ISBN: (纸本)9781509018178

In recent years the growth in quantity, diversity and capability of Earth Observation (EO) satellites, has enabled increase's in the achievable payload data dimensionality and volume. However, the lack of equivalent advancement in downlink technology has resulted in the development of an onboard data bottleneck. This bottleneck must be alleviated in order for EO satellites to continue to efficiently provide high quality and increasing quantities of payload data. This research explores the selection and implementation of state-of-the-art multidimensional image compression algorithms and proposes a new onboard data processing architecture, to help alleviate the bottleneck and increase the data throughput of the platform. The proposed new system is based upon a backplane architecture to provide scalability with different satellite platform sizes and varying mission's objectives. The heterogeneous nature of the architecture allows benefits of both Field Programmable Gate Array (FPGA) and Graphical processing Unit (GPU) hardware to be leveraged for maximised data processing throughput.

关键词： Onboard image Compression processing Earth Observation GPU FPGA

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Comparative Performance Study of Various Content Based image Retrieval Methods 1

引用

1st International conference on Information and Communication Technology for Intelligent systems (ICTIS)

作者： Shah, Rushabh Vaghela, Jeetendra Surve, Khyati Shah, Rutvi Sharma, Priyanka Mishra, Rasendu Patel, Ajay Datt, Rajan Nirma Univ Inst Technol Ahmadabad Gujarat India Shri Chimanbhai Patel Inst Comp Applicat Ahmadabad Gujarat India Raksha Shakti Univ Ahmadabad Gujarat India

ISBN: (数字)9783319309330

ISBN: (纸本)9783319309330;9783319309323

With the increase in the data storage and data acquisition technologies there is an increase in huge image database. Therefore we need to develop proper and accurate systems to manage this database. Here in this paper we focus on the transformation technique to search, browse and retrieve images from large database. Here we have discussed briefly about the CBIR technique for image retrieval using Discrete Cosine Transform for generating feature vector. We have researched on the different retrieval algorithms. The proposed work is experimented over 9000 images from MIRFLIKR Database (Huskies ACM International conference on Multimedia Information Retrieval (MIR'08), 2008 [1]). We have focused on showing the difference between the precision and recall and also the time of different methods and its performance by querying an image from the database and a non-database image.

关键词： Content based image retrieval image retrieval methods image processing techniques Digital image processing

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Abstracting Data and image processing systems using a Component-based Domain Specific Language 4

Abstracting Data and Image Processing Systems using a Compon...

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4th International conference on Model-Driven Engineering and Software Development (MODELSWARD)

作者： Hoegg, Thomas Koehler, Christian Kolb, Andreas Univ Siegen Comp Graph & Multimedia Syst Grp Hoelderlinstr 3 D-57076 Siegen Germany

ISBN: (纸本)9789897582325

This work proposes a textual and graphical domain-specific language (DSL) designed especially for modeling and writing data and image processing algorithms. Since reusing algorithms and other functionality leads to higher program quality and mostly shorter development time, this approach introduces a novel component-based language design. Special diagrams and structures, such as components, component-diagrams and component-instance-diagrams are introduced. The new language constructs allow an abstract and object-oriented description of data and image processing tasks. Additionally, a compatible graphical design interface is proposed, giving modelers and architects the opportunity to decide which kind of modeling they prefer (graphical or textual, including round-trip engineering).

关键词： Modeling Components Domain-specific Languages image processing

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Automated processing of Cytological and Histological images 12

Automated Processing of Cytological and Histological Images

引用

12th International conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Berezsky, Oleh Pitsun, Oleh Ternopil Natl Econ Univ CIT Dept Lvivska St 11 Ternopol Ukraine

The paper analyzes well-known automated microscopy systems. The work presents the comparative analysis of low-and middle-designed algorithms. The adaptive module of pre-processing and image segmentation has been worke... 详细信息

ISBN: (纸本)9786176079132

关键词： automated microscopy system algorithm image preprocessing and segmentation

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Supervised sparse-representation classification on hyperspectral images using the city-block distance to improve performance

Supervised sparse-representation classification on hyperspec...

引用

8th International conference of Pattern Recognition systems (ICPRS 2017)

作者： Fernando X. Arias Heidy Sierra Luis O. Jimenez-Rodriguez Emmanuel Arzuaga Universidad de Puerto Rico San Juan PR

ISBN: (纸本)9781785616525

Hyperspectral images' data structure contains information from spectral ranges far beyond the limits of conventional, visible light imaging devices. This additional information comes at the cost of having unwieldy large image sizes, which presents an important computational resource consideration for many applications. Recent studies have shown that the usual large amount of redundancy in Hyperspectral images can be discarded to avoid classification noise by means of sparse signal processing principles. To improve on classification performance, class-dependent Sparse-Representation classification (cd-SRC) algorithm includes Euclidean distance information between the sparse representation of a sample pixel to be classified and the training classes. The current work describes the use of Manhattan (or City Block) distance for improving the cd-SRC classification procedure. Our results show that classification performance using Euclidean Distance is comparable to the Manhattan Distance metric, which requires a smaller number of significantly less computationally expensive operations. In addition, we show that sparse representation classification has a significant advantage in classification performance compared to established Hyperspectral image classification algorithms, such as the well-known Minimum Euclidean Distance and Support Vector Machine classifiers.

关键词： compressed sensing data structures hyperspectral imaging image classification visible spectra hyperspectral imagery VISIBLE SPECTRUM Data structures Compressed sensing image classification Euclidean distance sparse representation Taxonomy Manhattan city blocks Support Vector Network

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A Highly Accelerated Parallel Multi-GPU based Reconstruction Algorithm for Generating Accurate Relative Stopping Powers

A Highly Accelerated Parallel Multi-GPU based Reconstruction...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Paniz Karbasi Ritchie Cai Blake Schultze Hanh Nguyen Jones Reed Patrick Hall Valentina Giacometti Vladimir Bashkirov Robert Johnson Nick Karonis Jeffrey Olafsen Caesar Ordonez Keith E. Schubert Reinhard W. Schulte Department of Electrical and Computer Engineering Baylor University Waco TX USA Center for Medical Radiation Physics University of Wollongong Wollongong NSW Australia Loma Linda University Loma Linda CA Santa Cruz Institute for Particle Physics University of California Santa Cruz CA USA Department of Computer Science Northern Illinois University DeKalb IL Department of Physics Baylor University Waco TX USA

ISBN: (纸本)9781538622834

Low-dose Proton Computed Tomography (pCT) is an evolving imaging modality that is used in proton therapy planning which addresses the range uncertainty problem. The goal of pCT is generating a 3D map of relative stopping power measurements with high accuracy within clinically required time frames. Generating accurate relative stopping power values within the shortest amount of time is considered a key goal when developing an image reconstruction software. The existing image reconstruction softwares have successfully met this time frame and even exceeded this time goal, but require clusters with hundreds of processors. This paper describes a novel reconstruction technique using two graphics processing unit devices. The proposed reconstruction technique is tested on both simulated and experimental datasets and on two different systems namely Nvidia K40 and P100 graphics processing units from IBM and Cray. The experimental results demonstrate that our proposed reconstruction method meets both the timing and accuracy with the benefit of having reasonable cost and efficient use of power.

关键词： Protons image reconstruction Graphics processing units Runtime Iterative algorithms Reconstruction algorithms

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