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

共 12675 条记录，以下是4511-4520 订阅

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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...

引用

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...

引用

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

引用

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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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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Parallel algorithms for acoustic processing of speech signals

Parallel algorithms for acoustic processing of speech signal...

引用

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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image scanning techniques for speeded-up color object detection 5th

Image scanning techniques for speeded-up color object detect...

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5th Eccomas Thematic conference on Computational Vision and Medical image processing, Vipimage 2015

作者： Trifan, Alina Neves, António J. R. Cunha, Bernardo Department of Electronics and Telecommunications Engineering Intelligent Systems and Intelligent Robotics Laboratory Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal

ISBN: (纸本)9781138029262

Nowadays there are many computer vision algorithms dedicated to solve the problem of object detection, from many different perspectives. Many of these algorithms take a considerable processing time even for low resolution images. Research areas that are more concerned about real-time capabilities of a system, such as the case of robotics for example, are focusing on adapting the existing algorithms or developing new ones that cope with time constraints. Color object detection algorithms are often used in time-constrained application since the color of an object is an important clue for its detection. In addition, color segmentation algorithms have a smaller computational cost than generic object detection algorithms. Most of the color object detection algorithms include a step of image scanning in search of pixels of the color of interest. In this paper we present a study on the influence of an image scanning pattern while searching for pixels of a certain color versus the image resolution in the results of three color object detection algorithms. We present results comparing different scanning approaches versus different resolution images for color object detection algorithms based on blob formation, contours detection and region growing clustering. Our experiments show that using search lines for color segmentation, followed by blob formation provides faster and more accurate results. © 2016 Taylor & Francis Group, London.

关键词： Color

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SPEED: Open-Source Framework to Accelerate Speech Recognition on Embedded GPUs

SPEED: Open-Source Framework to Accelerate Speech Recognitio...

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Euromicro Symposium on Digital System Design

作者： Syed Mohammad Asad Hassan Jafri Ahmed Hemani Leonardo Intesa Royal Institute of Technology (KTH) Sweden

Due to high accuracy, inherent redundancy, and embarrassingly parallel nature, the neural networks are fast becoming mainstream machine learning algorithms. However, these advantages come at the cost of high memory and processing requirements (that can be met by either GPUs, FPGAs or ASICs). For embedded systems, the requirements are particularly challenging because of stiff power and timing budgets. Due to the availability of efficient mapping tools, GPUs are an appealing platforms to implement the neural networks. While, there is significant work that implements the image recognition (in particular Convolutional Neural Networks) on GPUs, only a few works deal with efficiently implement of speech recognition on GPUs. The work that does focus on implementing speech recognition does not address embedded systems. To tackle this issue, this paper presents SPEED (Open-source framework to accelerate speech recognition on embedded GPUs).We have used Eesen speech recognition framework because it is considered as the most accurate speech recognition technique. Experimental results reveal that the proposed techniques offer 2.6X speedup compared to state of the art.

关键词： Computer architecture Speech recognition Microprocessors Graphics processing units Neural networks Parallel processing Speech

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