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

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A Survey of Blob Detection algorithms for Biomedical images

A Survey of Blob Detection Algorithms for Biomedical Images

引用

International conference of Information and Communication Technology for Embedded systems

作者： Kay Thwe Min Han Bunyarit Uyyanonvara School of Information Computer and Communication TechnologySirindhorn International Institute of Technology Thammasat University 131 Moo 5 Tiwanont Road Bangkadi Muang Pathumthani 12000 Thailand School of Information Computer and Communication Technology Sirindhorn International Institute of Technology Thammasat University 131 Moo 5 Tiwanont Road Bangkadi Muang Pathumthani 12000 Thailand

ISBN: (纸本)9781509022502

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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Euclidean Proximity Function in image processing

Euclidean Proximity Function in Image Processing

引用

IEEE Signal processing algorithms, Architectures, Arrangements, and Applications conference

作者： Pawel M. Stasik Poznan University of Technology Faculty of Computing Science Chair of Control and Systems Engineering

ISBN: (纸本)9781509026616

In image processing measuring and valuing a distance between two points is important. The obtained values can be used for determining whether two points are close to each other or to define weights for a filter concentrated around a central element. While there are measures of proximity, neither of them was defined with a such use in mind, mostly concentrating on problem of an optimization. The idea is to turn the Euclidean distance between two points into a measure of how close (or far) two points are from each other, basing on two given ranges. The function was mostly obtained by a theoretical analysis supported with a mathematical calculation and examples of use. As it was proven in the work, the obtained function can be implemented not only to measure proximity, but also as a flexible kernel for image filters, allowing for blurring or edge-detection.

关键词： image edge detection Euclidean distance Fuzzy logic Limiting Hypercubes Optimization Edge detection Euclidean distance Hypercube Limiting Fuzzy logic image processing image filtering Proximity central element Function BLURRING

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Pulse rate variability and blood oxidation content identification using miniature wearable wrist device

Pulse rate variability and blood oxidation content identific...

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International conference on systems, Signals and image processing, IWSSIP

作者： Jernej Ženko Marko Kos Iztok Kramberger Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

This paper presents the work related to the identification of PRV (pulse rate variability) and SpO2 (blood oxidation content) using miniature wearable wrist device. The extension of currently widely used PPT (photo plethysmography) measuring technique is proposed. Most PPT devices only measure PR (pulse rate), but with minimum adaptations to the sensor, a wider range of parameters can be measured. Two of such parameters are PRV and SpO2. This set of parameters gives a better insight into ones physical and mental state than only PR parameter. In order to develop a device that does not obstruct the user in any way, we propose a miniature non-invasive wearable device, and algorithms that do not need any significant processing power in order to identify the biometric parameters. The device is a lightweight battery powered embedded system, that measures and analyses biometric data for later analysis in correlation with one's activity.

关键词： Decision support systems Data processing

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Novel approach to enhance face recognition using depth maps

Novel approach to enhance face recognition using depth maps

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International conference on systems, Signals and image processing, IWSSIP

作者： Yaser Saleh Eran Edirisinghe Department Computer Science Loughborough University Loughborough UK

ISBN: (纸本)9781467395564

Face recognition, although being a popular area of research and study, still has many challenges, and with the appearance of the Microsoft Kinect device, new possibilities of research were uncovered, one of which is face recognition using the Kinect. With the goal of enhancing face recognition, this paper is aiming to prove how depth maps, since not effected by illumination, can improve face recognition with a benchmark algorithm based on the Eigenface. This required some experiments to be carried out, mainly in order to check if algorithms created to recognize faces using normal images can be as effective if not more effective with depth map images. The OpenCV Eigenface algorithm implementation was used for the purpose of training and testing both normal and depth-map images. Finally, results of the experiments are presented to prove the ability of the tested algorithm to function with depth maps, also, proving the capability of depth maps face recognition's task in poor illumination.

关键词： Face recognition Lighting Face Training image recognition Benchmark testing

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International conference on Modern Engineering: Science and Education, MESE 2011

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International conference on Modern Engineering: Science and Education, MESE 2011

ISBN: (纸本)9783319295787

The proceedings contain 19 papers. The special focus in this conference is on Advances in Mechanical Engineering. The topics include: Frameworks not restorable from self stresses;structural modifications synthesis of bennett mechanism;kinematic research of bricard linkage modifications;drive selection of multidirectional mechanism with excess inputs;engineering calculations of bolt connections;modern methods of contact forces between wheelset and rails determining;a novel design of an electrical transmission line inspection machine;one stable scheme of centrifugal forces dynamic balance;new effective data structure for multidimensional optimization orthogonal packing problems;one-dimensional models in turbine blades dynamics;stationary oscillation in two-mass machine aggregate with universal-joint drive;the vibrations of reservoirs and cylindrical supports of hydro technical constructions partially submerged into the liquid;mathematical modelling of interaction of the biped dinamic walking robot with the ground;programmable movement synthesis for the mobile robot with the orthogonal walking drivers;processing of data from the camera of structured light for algorithms of image analysis in control systems of mobile robots;structural and phase transformation in material of steam turbines blades after high-speed mechanical effect;stress corrosion cracking and electrochemical potential of titanium alloys;metal flow control at processes of cold axial rotary forging and use of the capabilities of acoustic-emission technique for diagnostics of separate heat exchanger elements.

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algorithms for image processing in graph-based volumetric segmentation

Algorithms for image processing in graph-based volumetric se...

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International conference on Information, Intelligence, systems and Applications (IISA)

作者： Dumitru Dan Burdescu Liana Stanescu Marius Brezovan Cosmin Stoica Spahiu Florin Slabu Computers and information Technology Department University of Craiova Universitatea din Craiova Craiova RO Departament of Computer Science University of Craiova Craiova Dolj Romania

ISBN: (纸本)9781509034307

The aim of this article is to present a method to detect visual objects from color digital images by volumetric segmentation. We will discuss algorithms for visual and multimedia computing. The problem of partitioning images into homogenous regions or semantic entities is a basic problem for identifying relevant objects. The presented method is a general-purpose volumetric segmentation method and it produces results from two different perspectives: (a) from the perspective of perceptual grouping of regions from the images, and also (b) from the perspective of determining regions if the input spatial images contain visual objects. We present a unified framework for volumetric image segmentation and prism cells used is the first run into volumetric segmentation algorithms. The major concept used in graph-based volumetric segmentation method is the concept of homogeneity of volumes and thus the edge weights are based on color distance. The complexity of our original algorithm for volumetric segmentation is linear.

关键词： image segmentation image color analysis Visualization Partitioning algorithms Syntactics Vegetation Joining processes

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Efficient GPU Computing Framework of Cloud Filtering in Remotely Sensed image processing

Efficient GPU Computing Framework of Cloud Filtering in Remo...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Jing Ke Arcot Sowmya Yi Guo Tomasz Bednarz Michael Buckley School of Computer Science and Engineering UNSW / DATA61 CSIRO Sydney Australia School of Computer Science and Engineering UNSW Sydney Australia Mathematics Western Sydney University Sydney Australia DATA61 CSIRO Brisbane Australia DATA61 CSIRO Sydney Australia

For optical remote sensing images, an effective method to reduce or eliminate the impact of clouds is important. With big data input and real-time processing demands, efficient parallelization strategies are essential for high performance computing on multi-core systems. This paper proposes an efficient high performance parallel computing framework for cloud filtering and smoothing. A comparison and benchmarking of two parallel algorithms for cloud filtering that incorporates spatial smoothing solved by two-dimensional dynamic programming is implemented. The experiments were carried out on an NVIDIA GPU accelerator with evaluations of approximation, parallelism and performance. The test results show significant performance improvements with high accuracy compared with sequential CPU implementation, and can be applied to other multi-core systems.

关键词： Graphics processing units Smoothing methods Dynamic programming Indexes Instruction sets Heuristic algorithms Parallel processing

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Distributed optimization problem for second-order multi-agent networks with only position interaction 35

Distributed optimization problem for second-order multi-agen...

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第35届中国控制会议

作者： TRAN Ngoc-Tu LIU Xiao-Kang WANG Yan-Wu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Provincial Collaborative Innovation Center for New Energy Microgrid China Three Gorges University

ISBN: (纸本)9781509009107

In this paper, distributed optimization problem is investigated under a second-order multi-agent network, in which each agent is described as the double integrator. The multi-agent network is introduced for solving a large scale optimization problem by the cooperation of coupled agents. Based on the interaction over the network, the optimal solution of the problem can be obtained. Since the existing distributed algorithms for second-order multi-agent network enforce each agent to transmit complete information(both state information and derivation information of the independent variable, i.e., corresponded position and velocity information of the agent), this paper is motivated to design the distributed algorithm with only using the position information of neighbors, which reduces the requirement on communication bandwidth. With the help of Lyapunov analysis and La Sallel's Invariance Principle, the optimal solution is derived and the optimization problem is solved via the second-order multi-agent network. Finally, a numerical example is presented to illustrate the theoretical result.

关键词： Second-order multi-agent networks Distributed optimization Consensus

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A pipelined multi-softcore approach for the HOG algorithm

A pipelined multi-softcore approach for the HOG algorithm

引用

conference on Design and Architectures for Signal and image processing

作者： José Arnaldo Mascagni de Holanda João Manuel Paiva Cardoso Eduardo Marques Federal Institute of São Paulo Brazil Universidade do Porto Porto Porto PT University of Sao Paulo S??o Carlos Brazil

ISBN: (纸本)9781509030859

This paper describes the mapping and the acceleration of an object detection algorithm on a multiprocessor system based on an FPGA. We use HOG (Histogram of Oriented Gradients), one of the most popular algorithms for detection of different classes of objects and currently being used in smart embedded systems. The use of HOG on such systems requires efficient implementations in order to provide high performance possibly with low energy/power consumption budgets. Also, as variations and adaptations of this algorithm are needed to deal with different scenarios and classes of objects, programmability is required to allow greater development flexibility. In this paper we show our approach towards implementing the HOG algorithm into a multi-softcore Nios II based-system, bearing in mind high-performance and programmability issues. By applying source-to-source transformations we obtain speedups of 19× and by using pipelined processing we reduce the algorithms execution time 49×. We also show that improving the hardware with acceleration units can result in speedups of 72.4× compared to the embedded baseline application.

关键词： Histograms Support vector machines Parallel processing Field programmable gate arrays Program processors Object detection Hardware

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BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising

BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoi...

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IEEE International conference on Multimedia and Expo Workshops (ICMEW)

作者： Christopher A. Metzler Arian Maleki Richard G. Baraniuk Department of Electrical and Computer Engineering Rice University Department of Statistics Columbia University

ISBN: (纸本)9781509015535

The explosion of computational imaging has seen the frontier of image processing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a corresponding research thrust into non-linear image recovery algorithms, but in many ways this research is stuck where linear problem research was twenty years ago: Models, if used at all, are simple designs like sparsity or smoothness. In this paper we use denoisers to impose elaborate and accurate models in order to perform inference on generalized linear systems. More specifically, we use the state-of-the-art BM3D denoiser within the Generalized Approximate Message Passing (GAMP) framework to solve compressive phase retrieval. Our method demonstrates recovery performance equivalent to existing techniques using fewer than half as many measurements. This dramatic improvement in compressive phase retrieval performance opens the door for a whole new class of imaging systems.

关键词： image coding Approximation algorithms Imaging Message passing Signal processing algorithms Noise reduction Algorithm design and analysis

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