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ISA/IEEE Sensors for Industry Conference

作者： S. Cermak G. Brasseur H. Zangl P.L. Fulmek Institute of Electrical Measurement and Measurement Signal Processing Graz University of Technology Graz Austria Christian Doppler Laboratory for Automotive Measurement Research at the Institute of Industrial Electronics and Material Science University of Technology Vienna Vienna Austria

This paper presents a new approach for the design of incremental angular position and angular speed sensors, using a capacitive technology. Transmitter and receiver segments are integrated with the sensor electronics on a single PCB. As the sensor measures the change of capacitance in dependence of the rotor position, any conductive or dielectric material can be used for the gear-tooth rotor. The carrier frequency excitation and the differential sensor output assure a high level of EMC.

关键词： Capacitive sensors Magnetic sensors Velocity measurement Materials science and technology Electromagnetic compatibility Electric variables measurement Frequency Optical sensors Magnetic materials Transmitters

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Non independent strategies for blind source separation in functional MRI

Non independent strategies for blind source separation in fu...

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International Conference on Neural Information processing

作者： J.C. Rajapakse A. Cichocki K. Siwek School of Computer Engineering Nanyang Technological University Singapore Laboratory of Advanced Brain Signal Processing Brain Science Institute RIKEN Japan Institute of Electrical Engineering and Measurements Warsaw University of Technology Poland

This paper explores spatial decomposition of functional MR images by several extended blind source separation (BSS) techniques in order to detect the brain activation. The four techniques are based on different criteria and assumptions like mutual statistical independence or non-Gaussianity of sub-band sources, spatial linear predictability, spatial-temporal decorrelation and non-stationarity of the colored sources. We conclude that the detection of activation in fMRI experiments is possible in many cases by exploiting these characteristics of the sources extracted from raw data.

关键词： Blind source separation Magnetic resonance imaging Independent component analysis Source separation Data analysis Multidimensional signal processing Laboratories Electric variables measurement Decorrelation Data mining

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The design and implementation of a Chinese financial invoice recognition system

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Journal of Quantitative Linguistics 2002年第1期9卷 19-33页

作者： Ming, Delie Liu, Jian Tian, Jinwen State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

This paper designs and implements a financial invoice recognition system based on the features of the Chinese financial invoice. By using the linear whole block moving method in each vertical segment, a new fast algorithm is put forth to detect and rectify the slant image. To distinguish the different form types (the foundation necessary for locating the form fields, filtering the form lines, etc.), several representative form features are discussed and an invoice-type features library is built by using a semi-automatic machine study method. On the basis of the recognized invoice type, real invoice form is re-oriented against the corresponding blank form according to the invoice type feature, solving the problem of adhesion of characters and form lines, as well as the problem of character segmentation and recognition. Based on the Chinese financial invoice image feature, a mutual rectification mechanism founded on the recognition results of Chinese financial characters and Arabic numerals is put forward to raise the recognition rate. Finally, the experimental results and conclusions are presented. © Swets & Zeitlinger.

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Text scanner with text detection technology on image sequences

Text scanner with text detection technology on image sequenc...

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International Conference on Pattern Recognition

作者： Keechul Jung Kwang In Kim T. Kurata M. Kourogi JungHyun Han Pattern Recognition and Image Processing Laboratory Michigan State University USA Artificial Intelligence Laboratory KAIST South Korea National Institute for Advanced Industrial Science and Technology Japan School of Electrical and Computer Engineering Sung Kyun Kwan University South Korea

ISBN: (纸本)076951695X

We propose a text scanner which detects wide text strings in a sequence of scene images. For scene text detection, we use a multiple-CAMShift algorithm on a text probability image produced by a multi-layer perceptron. To provide enhanced resolution of the extracted text images, we perform the text detection process after generating a mosaic image in a fast and robust image registration method.

关键词： image sequences Layout image registration Cameras Parameter estimation Videos Pixel image processing Robustness Optical character recognition software

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Eurasip Journal on Applied signal processing: Editorial

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Eurasip Journal on Applied signal processing 2002年第10期2002卷 1003-1004页

作者： Strintzis, Michael G. Marques, Ferran Lavagetto, Fabio Information Processing Laboratory Electrical Engineering Department Aristotle University of Thessaloniki Thessaloniki 54006 Greece Informatics and Telematics Institute 1st Km Thermi-Panorama Road Thermi-Thessaloniki 57001 Greece Technical University of Catalonia UPC Campus Nord Modul D5 C/ Jordi Cirona 1-3 08034 Barcelona Spain Department of Communication DIST University of Cenova Via Opera Pia 13 Genova Italy Electrical Engineering Department University of Pittsburgh Pittsburgh PA United States University of Thessaloniki Thessaloniki Greece Info./Telematics Research Institute Thessaloniki Greece Swiss Fed. Institute of Technology EPFL Lausanne Switzerland Department of Signal Theory Polytechnic University of Catalonia Barcelona Spain Sign. and Image Processing Institute USC Los Angeles CA United States UPC Bercelona Spain AT and T Bell Laboratories Holmdel NJ United States University of Parma Parma Italy DIST University of Genova Genova Italy

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Terrain Simplification Research in Augmented Scene Modeling

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Journal of China University of Geosciences 2001年第4期12卷 351-355页

作者： Ming Delie You Kefei Tian Jinwen Liu Jian State Key laboratory for image processing and Intelligent Control, institute for Pattern Recognition and Artificial Intelligence , Huazhong University of science and technology , Wuhan 430074 Wang Guangju State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

关键词： augmented reality scene modeling terrain simplification triangulated irregular network importance measures local entropy.

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A general multisource contextual classification model of remotely sensed imagery based on MRF

A general multisource contextual classification model of rem...

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GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas

作者： R. Khedam A. Belhadj-Aissa Image Processing Laboratory Electronic Institute Faculty of Electrical Engineering Technology and Science University Algiers Algeria

ISBN: (纸本)0780370597

In this paper, we present a general model for contextual multisource and multitemporal classification of satellite imagery based on the Markov random field (MRF). For many remote sensing applications, the robust interpretation and evaluation of remote sensed images require the use of multiple sources of information available about the scene under consideration. Indeed, data provided by individual sensors is incomplete, inconsistent or imprecise. Additional sources may provide complementary information and the fusion of multisource data can create a more consistent interpretation of the scene in which the associated uncertainty is decreased and the reliability of analysis results is increased. Also, temporal data from a single sensor can be considered as separate information sources. The combination of multitemporal data sets over the same scene enhances information on changes that might have occurred in the area observed over time. From all these available data, our objective is to extract more information and achieve greater accuracy in assigning images to thematic classes. The multisource classification model employs a pixel by pixel classification technique that defines the interaction between the different sensors in terms of a sum of sensor specific energy function allowed by MRF. Each sensor is associated with a sensor specific reliability factor. The multitemporal classification model requires the integration into the classification process of the temporal information expressed in terms of transition probabilities from one class at time t-1 to another class at time t according to MRF. The contextual classification model deals with the problem of incorporating into the classification process the contextual information expressed in terms of the spatial interaction that exists between one pixel and pixels in the rest of the scene. This interaction is well modelled by MRF via the Gibbs distribution and Potts model. The general model is tested on three data sets f

关键词： Context modeling Remote sensing Layout Satellites Markov random fields Robustness Information resources Uncertainty Information analysis Data mining

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Local adaptive transform based image denoising with varying window size

Local adaptive transform based image denoising with varying ...

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IEEE International Conference on image processing

作者： H. Oktem V. Katkovnik K. Egiazarin J. Astola Signal Processing Laboratory Tampere Universty of Technology Tampere Finland Department of Mechatronics Kwangju Institute of Science and Technology Kwangju Republic of Korea

Local adaptive image denoising in transform domain is a powerful tool for adapting to unknown smoothness of the images. We propose to perform local adaptive denoising with adaptively varying local transform support size rather than using a transform with fixed size. We use a special rule (intersection of confidence intervals-ICI) to select the optimum window sizes locally. The algorithm provides significant improvements in the de-noising performance.

关键词： image denoising Noise reduction Wiener filter signal processing algorithms Filtering Wavelet domain Gaussian noise Adaptive filters Wavelet transforms Adaptive signal processing

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Mobility management and routing algorithms for soft handoff in wireless mobile data network using MGCP

Mobility management and routing algorithms for soft handoff ...

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IEEE Conference on Vehicular technology (VTC)

作者： Yong-I Kim Hwang Soo Lee Signal Processing Laboratory Korea Advanced Institute of Science and Technology Daejeon South Korea

We propose a soft handoff method in packet network for CDMA mobile station and three delay constrained routing algorithms for this application that find a tree between multiple sources and multiple destinations. The proposed algorithms, which provide guaranteed QoS (quality-of-service) services at the network layer, are also designed to find reduced-cost routing trees. The proposed algorithms are verified by simulation, and three algorithms' performances are compared in view of the total tree cost and maximum end-to-end delay.

关键词： Mobile radio mobility management Routing Intelligent networks Costs Delay Multicast algorithms signal processing algorithms Multiaccess communication Tree graphs Laboratories

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Generalized principal ratio combining for space-time codes in slowly fading channels

Generalized principal ratio combining for space-time codes i...

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IEEE Conference on Vehicular technology (VTC)

作者： Young Ju Kim Hwang Soo Lee Signal Processing Laboratory Korea Advanced Institute of Science and Technology Daejeon South Korea

We present a generalized version of principal ratio combining (PRC) proposed by Tarokh and Lo (see IEEE Communications Letters, vol.2, p.223-25, 1998), which is a near-optimum detection scheme for space-time codes in quasistatic flat fading environments. In Tarokh et al. work, the performance penalty increases as the number of receive antennas increases. In the proposed scheme, receive antennas are divided into K groups, and the PRC detection method is applied to each group. This shows a flexible tradeoff between performance and decoding complexity by choosing the appropriate K.

关键词： Space time codes Fading Receiving antennas Decoding Partial response channels Transmitting antennas Diversity reception Space technology signal processing Laboratories

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