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检索条件"任意字段=2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, CIISP 2007"

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A novel approach for edge detection based on the theory of electrostatic field

A novel approach for edge detection based on the theory of e...

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ieee International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Zhong-Ren Wang Yan-Ming Quan College of Mechanical Engineering South China University of Technology Guangzhou China

This paper proposed a novel, simple and effective edge detection algorithm basing on the Law of Coulomb. The algorithm assumes that each pixel is a point electric charge which exerts forces on other neighboring pixels and receives forces from the neighboring pixels. The attracting or excluding forces can be calculated by the law of Coulomb. The vector sum of all electrostatic forces is used to compute the magnitude and the direction of signal variation. Edges are characterized by high magnitude of electrostatic forces along a particular direction and can therefore be detected. The proposed algorithm was tested and compared with other common methods such as Prewitt, LOG, and Canny using Lena image, with and without the corruption of salt & pepper noise. Results show that the proposed edge detector is more robust under noisy condition. In addition, the algorithm can work at any desired scale through regulating the weighting coefficient.

关键词： image edge detection Electrostatics signal processing algorithms Detectors Noise robustness Communication systems Artificial intelligence Educational institutions Mechanical engineering Testing

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A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network

A Leaf Recognition Algorithm for Plant Classification Using ...

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ieee International symposium on signal processing and Information Technology (ISSPIT)

作者： Stephen Gang Wu Forrest Sheng Bao Eric You Xu Yu-Xuan Wang Yi-Fan Chang Qiao-Liang Xiang Institute of Applied Chemistry Chinese Academy and Sciences China Department of Computer Science Texas Tech University USA Department of Computer Science & Engineering Washington University of Saint Louis USA School of Information & Telecommunications Eng Nanjing University of Posts and Telecommunications China Department of Electronic Engineering National Taiwan University of Science and Technology Taiwan

In this paper, we employ probabilistic neural network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition for plant classification. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.

关键词： Classification algorithms Neural networks Feature extraction Artificial neural networks signal processing algorithms Shape Humans Biology computing Principal component analysis Computer science

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Twentieth ieee International symposium on Computer-Based Medical Systems-Title

Twentieth IEEE International Symposium on Computer-Based Med...

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Annual ieee symposium on Computer-Based Medical Systems

The following topics are dealt with: software systems in medicine and nursing; computer-aided diagnosis; knowledge-based systems & data mining; decision support systems; medical devices with embedded computers; signal and image processing in medicine; medical image segmentation & compression; medical and nursing informatics; network and telemedicine systems; telenursing systems; medical and nursing databases & information systems; web-based delivery of medical and nursing information; multimedia biomedical databases; content analysis of biomedical image data; hand-held computing applications in medicine; bioinformatics in medicine; medical intelligence; data warehousing.

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Simulation of LIDAR-based aircraft wake vortex detection using a bi-gaussian spectral model

Simulation of LIDAR-based aircraft wake vortex detection usi...

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ieee International symposium on Geoscience and Remote Sensing (IGARSS)

作者： Sebastien Lugan Laurent Bricteux Benoit Macq Piotr Sobieski Gregoire Winckelmans Damien Douxchamps Faculté des Sciences Appliquées Université Catholique de Louvain Belgium Nara Institute of Science and Technology Image Processing Laboratory Japan

A new spectral model of the return signal from a LIDAR Doppler wake vortex detector is proposed. It has been experimentally discovered during ground-based and flight test campaigns but suffered a lack of theoretical evidence. Using high resolution fluid simulations of wake vortices, we highlight the physical meaning of this model. Comparisons with the traditional single Gaussian model show the superiority of this new approach is consistent with previous experimental results.

关键词： Aircraft Atmospheric modeling Laser radar computational modeling Atmosphere Infrared detectors Wind speed Navier-Stokes equations image processing Laboratories

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Intelligent cameras and embedded reconfigurable computing: a case-study on motion detection

Intelligent cameras and embedded reconfigurable computing: a...

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ieee International symposium on System-on-Chip

作者： Claudio Mucci Luca Vanzolini Antonio Deledda Fabio Campi Gerard Gaillat ARCES University of Bologna Bologna Italy STMicroelectronics Agrate Italy THALES Optronique S.A. Guyancourt France

image processing for intelligent cameras like those used in video surveillance applications implies computational demanding algorithms activated in function of non predictable events, such as the content of the image or user requests. For such applications, hardwired acceleration must be restricted to a minimum subset of kernels, due to the increasing NREs when application update become necessary. Embedded reconfigurable processors, coupling in the same computing engine a general-purpose embedded processor and field-programmable fabrics, provide an appealing trade-off point between pure software and dedicated hardware acceleration. As a case-study, this paper presents the implementation of a set of image processing operators utilized for motion detection on the DREAM adaptive DSP. With respect to pure software solutions, the proposed implementation achieves a performance improvement of 2-3 orders of magnitude, while retaining the same degree of programmability and the same economical perspectives from the end-user point of view of processor-based approaches.

关键词： Smart cameras Embedded computing Motion detection computational intelligence image processing Application software Acceleration Video surveillance Computer applications Kernel

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Security and privacy protection for automated video surveillance

Security and privacy protection for automated video surveill...

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ieee International symposium on signal processing and Information Technology (ISSPIT)

作者： Nadia Baaziz Nathalie Lolo Oscar Padilla Felix Petngang Department of Computer Science and Engineering Université du Quàbec en Outaouais Gatineau Canada

In this paper, we present an automated video surveillance system designed to 1) ensure efficient selective storage of data, 2) provide means for enhancing privacy protection, and 3) secure visual data against malicious attacks. The proposed solution is a 3-module system processing captured video data before storage. Salient motion detection is used to retain relevant sequences and identify regions of interest with potential privacy-sensitive details. Then, an invertible and secure privacy preserving process is performed using a DCT-based scrambling technique on selected regions. To secure visual data and allow for data authentication, a self-embedding watermarking technique is applied on each image sequence. It offers the capability of proving authenticity as well as locating manipulated regions. Furthermore, this technique is also able to recover and reconstruct a good approximation of original lost content. In addition to a low computational complexity, simulation results show the effectiveness of the whole system in achieving its goals in terms of security and privacy enhancement of automated video surveillance data.

关键词： Protection Video surveillance Data security Data privacy Secure storage Storage automation Motion detection Authentication Watermarking image sequences

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computational load reduction for anomaly detection in hyperspectral images: An experimental comparative analysis

Computational load reduction for anomaly detection in hypers...

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ieee International symposium on Geoscience and Remote Sensing (IGARSS)

作者： N. Acito G. Corsini M. Diani Dipartimento di Ingegneria dellInformazione Università di Pisa Pisa Italy

In this manuscript we investigate the efficient implementation of anomaly detection strategies in hyperspectral images. We especially focus on methods to reduce the computational complexity for a fast implementation of the detection algorithms. In particular, we consider two strategies based on data fusion methods applied to the outputs of the optical heads of the hyperspectral sensor. Furthermore, we consider, two computationally efficient implementations of anomaly detection where the well known RX algorithm is applied to hyperspectral data after dimensionality reduction. The detection performances of the anomaly detection strategies are compared using real data acquired by the MIVIS sensor. An estimate of the reduction of the computational load achieved with the different techniques is also provided.

关键词： Hyperspectral imaging image analysis Hyperspectral sensors Detection algorithms Optical sensors Head Military computing computational complexity signal processing algorithms Surveillance

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Noise Reduction Approach for Decision Tree Construction: A Case Study of Knowledge Discovery on Climate and Air Pollution

Noise Reduction Approach for Decision Tree Construction: A C...

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ieee symposium on computational intelligence and Data Mining (CIDM)

作者： Kyoko Fukuda Department of Mathematics and Statistics Computer Science and Software Engineering University of Canterbury Christchurch New Zealand

Data mining is more effective on noisy time series with appropriate data pre-processing. Singular spectrum analysis (SSA) is explored as the noise reduction approach for a decision tree classifier for noisy data. SSA provides groups of additive components, from low to high frequency, by decomposing the noisy time series. In this study, the noisy climate data is decomposed by SSA and is used to construct decision trees to predict the carbon monoxide (CO) air pollution levels. Analysis shows that separating out seasons from the annual data helps the algorithm; the classification accuracy improvements vary by season, with the maximum improvement (from 60.7% to 77.3%) found in summer by removing 6.42% of the high frequency signals, while autumn showed no improvement. Examining decision tree structures provides threshold climate values that impact on different CO levels, e.g., a light wind speed of les 2.5 m/s and any level of temperature inversion formation is found to associate with the high CO level (> 0.70 mg/m 3 ). Overall, data pre-processing using SSA is encouraging to improve the results of any time series data mining approach. Examining decision trees of the climate and air pollution helps increase knowledge about the data, and the studied approaches can be adaptable for various future environmental studies

关键词： Noise reduction Decision trees Air pollution Data mining Frequency Classification tree analysis Additive noise Noise level Carbon dioxide signal analysis

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Real-time Feature Tracking on an Embedded Vision Sensor for Small Vision-guided Unmanned Vehicles

Real-time Feature Tracking on an Embedded Vision Sensor for ...

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ieee International symposium on computational intelligence in Robotics and Automation (CIRA)

作者： Jonathan D. Anderson Dah-Jye Lee Barrett Edwards James Archibald Christopher R. Greco Electrical and Computer Engineering Department Brigham Young University Provo UT USA

Small unmanned vehicles (UVs) are seeing more widespread use In military, scientific, and civil sectors in recent years. Because of the limitations inherent in small UVs, including power consumption and payload, the selection of light weight and low power sensors and processors becomes critical. Low power CMOS cameras and real-time vision processing algorithms can provide fast and reliable information to the UVs. These vision algorithms often require computational power that limits their use in traditional general purpose processors using conventional software. The latest developments in field programmable gate arrays (FPGAs) provide an alternative for hardware and software co-design of complicated real-time vision algorithms. Many vision algorithms utilize image features as the main source of information. By tracking features from one frame to another, it becomes possible to perform many different high-level vision tasks. This paper describes a feature tracking algorithm and an FPGA hardware implementation that operates in real-time.

关键词： Vehicles Field programmable gate arrays Software algorithms Hardware Energy consumption Payloads CMOS process CMOS image sensors Cameras Computer vision

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A FINITE ELEMENT METHOD FOR ELASTIC PARAMETERIZATION AND ALIGNMENT OF CORTICAL SURFACES USING SULCAL CONSTRAINTS

A FINITE ELEMENT METHOD FOR ELASTIC PARAMETERIZATION AND ALI...

引用

ieee International symposium on Biomedical Imaging

作者： Anand A. Joshi David W. Shattuck Paul M. Thompson Richard M. Leahy Signal and Image Processing Institute University of Southern California Los Angeles CA USA Laboratory of Neuro Imaging University of California Los Angeles CA USA

ISBN: (纸本)9781424406715;1424406714

We present a cortical surface registration method that simultaneously aligns sulcal landmarks and parameterizes two cortical surfaces. The approach is based on coregistration of cortical surface coordinate systems so that the labeled sulcal features share the same coordinates on both cortical surfaces. We model the cortex as an elastic sheet and solve the associated Cauchy-Navier equilibrium equation subject to sulcal alignment constraints. The elastic energy is computed directly with respect to the intrinsic surface geometry and discretized using a finite element method on triangular tessellations of the two surfaces. In contrast to alternative methods for cortical alignment, the method avoids the need for an intermediate flat space for sulcal landmark matching and provides a fast, accurate and inverse-consistent surface registration and parameterization for inter-subject neuroanatomical studies

关键词： Finite element methods Equations computational efficiency Cost function Brain modeling signal processing image processing Laboratories Neuroimaging Vectors

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