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检索条件"主题词=change detection algorithms"

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An Intelligent Video Segmentation Algorithm in Rainy Situation

An Intelligent Video Segmentation Algorithm in Rainy Situati...

引用

International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Da-Jinn Wang Yan-Ting Ye Thou-Ho Chen Tsong-Yi Chen Department of Electronic Engineering National Kaohsiung University of Applied Sciences Kaohsiung Taiwan Department of Information Management National Kaohsiung Marine University Kaohsiung Taiwan

A novel video object segmentation algorithm based on object structure and chromatic analysis in the rainy situations is proposed in this paper. Firstly, we separate the pixels of both foreground and background from the image sequence by using the change-detection approach. Thus, we can obtain the initial mask of object, which consists of shadow regions and reflective regions on the wet ground. The shadow region is caused of the object projection and mirroring on the wet ground generates the reflective region. Both of two regions can be removed by analyzing the structure and color of the moving object. Finally, the boundary of moving object is refined by using connecting component labeling and morphological operations. Experimental results show that our proposed algorithm can efficiently extract the moving objects, especially under the rainy environments.

关键词： change detection algorithms Image segmentation Object segmentation Algorithm design and analysis Pixel Image sequences Image color analysis Joining processes Labeling Morphological operations

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Typical Behavior Patterns Extraction and Anomaly detection Algorithm Based on Accumulated Home Sensor Data

Typical Behavior Patterns Extraction and Anomaly Detection A...

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International Conference on Future Generation Communication and Networking (FGCN)

作者： Taketoshi Mori Akinori Fujii Masamichi Shimosaka Hiroshi Noguchi Tomomasa Sato Mechano-Informatics University of Tokyo Bunkyo Tokyo Japan

In this paper, we propose a method consists of two components, behavior patterns extraction and anomaly detection algorithm in daily life. To begin with, sensor data are accumulated in a room environment and behavior description labels are assigned for each data segment using HMM(hidden Markov model) and k-means method. An HMM is composed every day based on sensor data segments of the day. The behavior description label at each time segment is determined by likelihood of the segment computed using the HMM. In anomaly detection step, typical behavior sequences are acquired using probabilistic density of behavior occurrence and behavior successive time. Each probabilistic density is composed based on accumulating labeled- data using sequential discounting Laplace estimation and sequential discounting expectation and maximization algorithms. When a new datum comes, if typical behavior data change largely, the data is detected as anomaly. The proposed method is verified by a long-time activity detection sensor data taken at a house of elderly person.

关键词： Data mining detection algorithms Hidden Markov models Intelligent sensors Rhythm Sensor phenomena and characterization change detection algorithms Senior citizens Object detection Sensor systems

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On-Line Learning of Evolving Neural Models for Process Identification and Abnormality detection

On-Line Learning of Evolving Neural Models for Process Ident...

引用

International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Gancho Vachkov Department of Reliability-based Information Systems Engineering Kagawa University Takamatsu Kagawa Japan

In this paper a new algorithm for creating evolving neural models is proposed. Instead of repeating the "growing" and "pruning" steps during the learning, as in the most other known evolving algorithms, here we create a growing neural model from a fixed size data buffer and repeatedly check the model quality, in the sense of "average minimal distance" between the neurons and the data in this buffer. If the current neural model does not satisfy the required quality for the new on-line updated data buffer, then a new growing neural model is created from the updated data buffer. The new proposed algorithm is very efficient in computation cost. Its better performance is demonstrated by comparison with two other algorithms with preliminary fixed number of neurons, namely the standard non-evolving learning and the real-time evolving algorithm. The results show the applicability of the new algorithm for modeling and detection of changes and abnormalities in real-time evolving processes.

关键词： Neurons Computer buffers change detection algorithms Diesel engines Fault diagnosis Shape Information systems Reliability engineering Systems engineering and theory Cities and towns

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Thread-Sensitive Pointer Analysis for Inter-Thread Dataflow detection

Thread-Sensitive Pointer Analysis for Inter-Thread Dataflow ...

引用

IEEE Workshop on Future Trends of Distributed Computing Systems

作者： Ju Qian Baowen Xu School of Computer Science and Engineering South-East University Nanjing China Jiangsu Institution of Software Quality Nanjing China

Inter-thread dataflows are of great importance in analyzing concurrent programs. Suffering from the complexity of currency, it is still difficult to identify them from Java programs precisely and efficiently. A fundamental problem in inter-thread dataflow analysis is pointer analysis. Currently, pointer analyses can be classified into context-sensitive ones and context-insensitive ones. They are either too time consuming or too imprecise and hence not suitable for scalable and high precision inter-thread dataflow analysis. To change the situation, this paper proposes a thread-sensitive pointer analysis algorithm which only uses sequences of thread starts as calling contexts. As in inter-thread dataflow analysis, the major objective is analyzing interthread dataflows not intra-thread ones, the coarse-grained context-sensitivity can not only effectively speed up the analysis, but also preserve the analyze precision as much as possible

关键词： Data analysis Yarn Algorithm design and analysis Java Information analysis Concurrent computing Computer science Data engineering Software quality change detection algorithms

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Radiometric recalibration procedure for landsat-5 thematic mapper data

Radiometric recalibration procedure for landsat-5 thematic m...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gyanesh Chander Esad Micijevic Ronald W. Hayes Julia A. Barsi USGS EROS Sioux Falls Science Applications International Corporation SD USA Science Systems and Applications NASA Goddard Space Flight Center Greenbelt MD USA

The landsat-5 (L5) satellite was launched on March 01, 1984, with a design life of three years. Incredibly, the L5 thematic mapper (TM) has collected data for 23 years. Over this time, the detectors have aged, and its radiometric characteristics have changed since launch. The calibration procedures and parameters have also changed with time. Revised radiometric calibrations have improved the radiometric accuracy of recently processed data; however, users with data that were processed prior to the calibration update do not benefit from the revisions. A procedure has been developed to give users the ability to recalibrate their existing level 1 (L1) products without having to purchase reprocessed data from the U.S. geological survey (USGS). The accuracy of the recalibration is dependent on the knowledge of the prior calibration applied to the data. The "work order" file, included with standard national land archive production system (NLAPS) data products, gives parameters that define the applied calibration. These are the internal calibrator (IC) calibration parameters or the default prelaunch calibration, if there were problems with the IC calibration. This paper details the recalibration procedure for data processed using IC, in which users have the work order file.

关键词： Radiometry Satellites Remote sensing Calibration Detectors Table lookup Lamps Instruments Geology change detection algorithms

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Estimation of power system parameters based on load variance observations - laboratory studies

Estimation of power system parameters based on load variance...

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International Conference on Electrical Power Quality and Utilisation (EPQU)

作者： Andrzej Bien Dariusz Borkowski Andrzej Wetula Department of Measurement and Istrumentation AGH University of Science and Technology Krakow Poland

The paper concerns important problem: estimation of power system equivalent parameters. Knowledge of these parameters is needed to determine disturbances propagation ability through power grid. Authors present new techniques, which may significantly improve accuracy of noninvasive power system identification. These are: voltage and current coherent resampling algorithm, which ensures that sampling frequency match actual fundamental frequency of power system, so the DFT analysis is almost leakage-free; envelope detection algorithm which allows to estimate equivalent impedance of the load and its variability for fundamental frequency; the method of load change detection ensuring that only fragments having sufficient amount of information for power system identification will be used in parameters estimation. The proposed methods were tested using laboratory power system model of known parameters. Presented results of laboratory experiments confirmed correctness of the described methods.

关键词： Power systems Laboratories Frequency estimation Power system analysis computing Power system modeling Power grids Voltage change detection algorithms Sampling methods Information analysis

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Fusion of background estimation approaches for motion detection in non-static backgrounds

Fusion of background estimation approaches for motion detect...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Eduardo Monari Charlotte Pasqual Institute for Information and Data Processing Karlsruhe Germany

detection of moving objects is a fundamental task in video based surveillance and security applications. Many detection systems use background estimation methods to model the observed environment. In outdoor surveillance, moving backgrounds (waving trees, clutter) and illumination changes (weather changes, reflections, etc.) are the major challenges for background modelling and the development of a single model that fulfils all these requirements is usually not possible. In this paper we present a background estimation technique for motion detection in non-static backgrounds that overcomes this problem. We introduce an enhanced background estimation architecture with a long-term model and a short-term model. Our system showed that fusion of the detections of these two complementary approaches, improves the quality and reliability of the detection results.

关键词： Motion estimation Motion detection change detection algorithms Pixel Surveillance Lighting Layout Power system modeling Optical reflection Density functional theory

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Computation of the One-Dimensional Unwrapped Phase

Computation of the One-Dimensional Unwrapped Phase

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International Conference on Digital Signal Processing (DSP)

作者： Zahi N. Karam Alan V. Oppenheim Digital Signal Processing Group Massachusetts Institute of Technology Cambridge MA USA

In this paper, the computation of the unwrapped phase of the discrete-time Fourier transform (DTFT) of a one-dimensional finite-length signal is explored. The phase of the DTFT is not unique, and may contain integer multiple of 2 pi discontinuities. The unwrapped phase is the instance of the phase function chosen to ensure continuity. This paper compares existing algorithms for computing the unwrapped phase. Then, two composite algorithms are proposed that build upon the existing ones. The core of the proposed methods is based on recent advances in polynomial factoring. The proposed methods are implemented and compared to the existing ones.

关键词： Signal processing algorithms Digital signal processing Cepstrum Phase detection Sampling methods Fourier transforms Poles and zeros change detection algorithms Phase frequency detector Signal processing

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Detecting Attacks in Routers Using Sketches

Detecting Attacks in Routers Using Sketches

引用

IEEE Workshop on High Performance Switching and Routing

作者： Dhiman Barman Piyush Satapathy Gianfranco Ciardo Department of Computer Science and Engineering University of California Riverside USA

Designing routers against different attacks is imperative in today's Internet. We propose accurate, memory efficient, and scalable techniques to detect attacks such as worms, viruses, superspreaders, and denials-of-service (DoS) in routers. Our schemes enable detection in the routers by looking only at the IP headers. We propose a general methodology to use sketches, in particular count-min sketch, FM sketch, and counting and multi-counting Bloom filters, to recognize attacks in the routing architecture. Our techniques are based on change detection, for which we propose an algorithm that can work on data-streams and leverage the accurate and efficient estimation provided by sketches. We evaluate the performance of different schemes on real traces to show their accuracy.

关键词： Computer worms Traffic control Filters change detection algorithms Telecommunication traffic Internet Principal component analysis Time series analysis Data structures

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Extraction of Embedded Class Information from Universal Character Pattern

Extraction of Embedded Class Information from Universal Char...

引用

International Conference on Document Analysis and Recognition

作者： S. Uchida M. Sakai M. Iwamura S. Omachi K. Kise Kyushu University Japan Osaka Prefecture University Japan University of Tohoku Japan

This paper is concerned with a universal pattern, which is defined as a character pattern designed to have high machine-readability. This universal pattern is a character pattern printed with stripes. The cross ratio calculated from the widths of the stripes represents the character class. Thus, if the boundaries of the stripes can be detected for measuring the widths, the class can be determined without ordinary recognition process. Furthermore, since the cross ratio is invariant to projective distortions, the correct class will be still determined under those distortions. This paper describes a practical scheme to recognize this universal pattern. The proposed scheme includes a novel algorithm to detect the stripe boundaries stably even from the universal pattern image contaminated by non-uniform lighting and noise. The algorithm is realized by a combination of a dynamic programming-based optimal boundary detection and a finite state automaton which represents the property of the universal pattern. Experimental results showed the proposed scheme could recognize 99.6% of the universal pattern images which underwent heavy projective distortions and non-uniform lighting.

关键词： Data mining Pattern recognition Gray-scale Character recognition Ubiquitous computing Cameras Optical character recognition software change detection algorithms Distortion measurement Pollution measurement

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