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

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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...

引用

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

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

Supervised sparse-representation classification on hyperspec...

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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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Automated processing of Cytological and Histological images 12

Automated Processing of Cytological and Histological Images

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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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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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Visual Clustering based on Kernel Sparse Representation on Grassmann Manifolds

Visual Clustering based on Kernel Sparse Representation on G...

引用

IEEE International conference on Cyber Technology in Automation, Control, and Intelligent systems

作者： Tianci Liu Zelin Shi Yunpeng Liu Key Laboratory of Opto-Electronic Information Processing CAS Shenyang 110016

ISBN: (纸本)9781538604915

image sets and videos can be modeled as subspaces which are actually points on Grassmann manifolds. Clustering of such visual data lying on Grassmann manifolds is a hard issue based on the fact that the state-of-the-art methods are only applied to vector space instead of non-Euclidean geometry. In this paper, we propose a novel algorithm termed as kernel sparse subspace clustering on the Grassmann manifold (GKSSC) which embeds the Grassmann manifold into a Reproducing Kernel Hilbert Space (RKHS) by an appropriate Gaussian projection kernel. This kernel is applied to obtain kernel sparse representations of data on Grassmann manifolds utilizing the self-expressive property and exploiting the intrinsic Riemannian geometry within data. Although the Grassmann manifold is compact, the geodesic distances between Grassmann points are well measured by kernel sparse representations based on linear reconstruction. With the kernel sparse representations, experimental results of clustering accuracy on the prevalent public dataset outperform state-of-the-art algorithms by more than 90 percent and the robustness of our algorithm is demonstrated as well.

关键词： Manifolds Kernel Clustering algorithms Sparse matrices Geometry Symmetric matrices Dictionaries Manifolds Kernel Symmetric matrix Seeds Dictionaries as Topic Sparse matrix Clustering algorithms geometry Non-Euclidean geometry Subspace

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Quantitative Characterization of Radiographic Weld Defect Based on the Ground Truth Radiographs Made on a Stainless Steel Plates 1

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3rd International conference on Information System Design and Intelligent Applications (INDIA)

作者： Chitra, P. Sathyabama Univ Fac Elect & Elect Madras 600119 Tamil Nadu India

ISBN: (数字)9788132227557

ISBN: (纸本)9788132227557;9788132227533

This paper presents a new approach for quantification of radiographic defects. This approach is based on calculating the size of the pixel using the known image quality indicator present in the radiographic image. This method is first applied on the ground truth realities of different shapes whose size is known in advance. The proposed method is then validated with the defect (porosity) where the defect is quantified accurately. The image processing techniques applied on the radiographic image are contrast enhancement, noise reduction and image segmentation to quantify the defects present in the radiographic image. The image processing algorithms are validated using image quality parameter Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

关键词： Defect quantification image quality indicator image processing Ground truth radiographs

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Parallel algorithms for acoustic processing of speech signals

Parallel algorithms for acoustic processing of speech signal...

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2016 IEEE International conference on Signal and image processing, ICSIP 2016

作者： Musaev, Muhammadjon Maxmudovich Raximov, Mexriddin Fazliddinovich Berdanov, Ulug'Bek Abdumurodovich O'Gli, Shukurov Kamoliddin Elbobo Dept. Computer Engineering Tashkent University of Information Technologies Tashkent Uzbekistan

ISBN: (纸本)9781509023769

In such computerized systems, such as voice control units, personal identification, IP-telephony, weapon control commands, accepting applications for reference services, automated stenography, recognition of individual words and phrases plays a major role in enhancing the effectiveness of technical systems. In the preliminary stages of speech processing algorithms for the allocation of phonetic characteristics is implemented, which are subjected to syntactic and semantic analysis in subsequent stages. To isolate the phonetic characteristics acoustic treatment is performed, which includes algorithms of pre-filtering, spectral analysis, segmentation, and a calculation of cepstral features. In this paper solves the problems of accelerated implementation of the acoustic processing algorithms in real-time systems, in which there is recognition of the individual teams. To implement the stream computing is used opportunities of C++ programming language and OpenMP technologies. To perform stream computing algorithms are used dual-core and multi-core processors. Obtained results of acceleration calculations correspond to the number of processor cores. © 2016 IEEE.

关键词： Real time systems

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