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检索条件"主题词=change detection algorithms"

共 1584 条记录，以下是371-380 订阅

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New Unsupervised change detection algorithm based on the MRF in remote sensing image

New Unsupervised change detection algorithm based on the MRF...

引用

Urban Remote Sensing Joint Event

作者： Lifei Wei Yanfei Zhong Liangpei Zhang Pingxiang Li National Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University of China Wuhan China

The most of traditional change detection methods are adopted to deal with the remote sensing images based on single threshold algorithm, the different threshold change information cannot be absolutely used, so it difficult to detect the complete information. To solve this problem, a new change detection algorithm based on the MRF is proposed in this paper. This method fully integrates the change information of each threshold change image, and the complete and accurate change information can be obtained. The experimental results suggest that the detection accuracy of this method in the paper, which has certain stability and intelligence outperform the traditional change detection methods.

关键词： Remote sensing Pixel change detection algorithms Image resolution Accuracy Joints Computational modeling

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High throughput sketch based online heavy change detection on FPGA

High throughput sketch based online heavy change detection o...

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International Conference on Reconfigurable Computing and FPGAs (ReConFig)

作者： Da Tong Viktor Prasanna Ming Hsieh Department of Electrical Engineering University of Southern California Los Angeles California

Significant changes in traffic patterns often indicate network anomalies. Detecting these changes rapidly and accurately is a critical task for network security. Due to the large number of network users and the high throughput requirement of today's networks, traditional per-item-state techniques are either too expensive when implemented using fast storage devices (such as SRAM) or too slow when implemented using storage devices with massive capacity (such as DRAM). Sketch, as a highly accurate data stream summarization technique, significantly reduces the memory requirements while supporting a large number of items. Sketch based techniques are attractive for exploiting the fast on-chip storage of state-of-the-art computing platforms to achieve high throughput. In this work, we propose a fully pipelined Sketch based architecture on FPGA for online heavy change detection. Our architecture forecasts the activity of the network entities based on their history, then reports the entities whose difference between their observed activities and the forecast activities exceed a given threshold. The post place-and-route results on a state-of-the-art FPGA show that our architecture sustains high throughput of 96 - 103 Gbps using various configurations of online heavy change detection.

关键词： Throughput change detection algorithms Mathematical model Field programmable gate arrays Memory management History

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change detection based on region likelihood ratio in multitemporal SAR images

Change detection based on region likelihood ratio in multite...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Yong-min Shuai Xin Xu Hong Sun Ge Xu Laboratory of Signal Processing Electronic Information School Wuhan University of China Wuhan China

In this paper, a novel approach for change detection in multitemporal synthetic aperture radar (SAR) images is presented. The proposed approach based on region likelihood ratio feature detection exploits an edge fusion technique for the SAR images segmentation. Segmentation is the key process in change detection based on region feature and the proposed edge fusion technique of two segmentation images ensures the accuracy of the changed parts segmentation. The change-detection process is divided into three main steps: 1 ) two SAR images segmentation based on watershed algorithm; 2) edge fusion of two segmentation images; 3) the region likelihood ratio feature extraction for changed region detection on the fusion result. Experimental results obtained on real SAR images acquired by the ERS-1 confirm the effectiveness of the proposed approach

关键词： Image segmentation Image edge detection Radar detection change detection algorithms Optical sensors Feature extraction Pixel Speckle Synthetic aperture radar Signal processing algorithms

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Adaptive Shot change detection Technique for Real-Time Operation on PMP

Adaptive Shot Change Detection Technique for Real-Time Opera...

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International Conference on Convergence Information Technology

作者： Won-Hee Kim Yong-Jae Jeong Kwang-Seok Moon Jong-Nam Kim Department of Electronic Computer Telecommunication Engineering Pukyong National University South Korea

Shot change detection is the main technique for automatic temporal segmentation of video. Until now, there were little research reports about real-time shot change detection for applying to hardware terminals with low performance such as PMPs (Portable Multimedia Player) and cellular phones. In this paper, we propose an adaptive real-time shot change detection algorithm using sub-sampling, weighting variance, and an adaptive threshold. We use weighting variance of frame difference for dividing feature extraction at a changed frame. We set an adaptive threshold using the average of variance from the next one of a last shot change frame to the previous one of a current frame. In the experiments, we obtained the detection rate of about 94.4% in overall accuracy. We verified real-time operation of shot change detection by implementing our algorithm on the TVUS HM-900 PMP from the company of Homecast. Therefore, our proposing algorithm will be helpful in searching video data on portable media player such as PMPs and cellular phones.

关键词： Gunshot detection systems Portable media players detection algorithms change detection algorithms Hardware Cellular phones Feature extraction Frequency domain analysis Cameras Histograms

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change detection and classification in brain MR images using change Vector Analysis

Change detection and classification in brain MR images using...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Rita Simoes Comelis Slump Signals and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente

ISBN: (纸本)9781424441211

The automatic detection of longitudinal changes in brain images is valuable in the assessment of disease evolution and treatment efficacy. Most existing change detection methods that are currently used in clinical research to monitor patients suffering from neurodegenerative diseases - such as Alzheimer's - focus on large-scale brain deformations. However, such patients often have other brain impairments, such as infarcts, white matter lesions and hemorrhages, which are typically overlooked by the deformation-based methods. Other unsupervised change detection algorithms have been proposed to detect tissue intensity changes. The outcome of these methods is typically a binary change map, which identifies changed brain regions. However, understanding what types of changes these regions underwent is likely to provide equally important information about lesion evolution. In this paper, we present an unsupervised 3D change detection method based on change Vector Analysis. We compute and automatically threshold the Generalized Likelihood Ratio map to obtain a binary change map. Subsequently, we perform histogram-based clustering to classify the change vectors. We obtain a Kappa Index of 0.82 using various types of simulated lesions. The classification error is 2%. Finally, we are able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.

关键词： Vector Analysis inspection methods change detection algorithms Brain Imaging Disease Progression automatic detection Cerebrum likelihood ratio Hemorrhage Treatment Effectiveness MAPPING(MATHEMATICAL) maps Clinical Study Neurodegenerative Diseases

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Polygon change detection for SPOT5 Color Image Using Multi-feature-clustering-analysis

Polygon Change Detection for SPOT5 Color Image Using Multi-f...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Wang Hua Pan Li Remote Sensing and Information School Wuhan University of China Wuhan China

This paper applies the multi-feature clustering analysis for SPOT5 color remote sensing images change detection based on image subtraction method and solves the problem of misjudge polygons. Subtraction chart is constructed by computing gray difference between pixels with a quite low threshold; Then, multi-feature-clustering-analysis is utilized to subtraction chart to delete misjudge polygons; Lastly, median filter and morphology algorithm are applied to remove noises caused by image registration and pixel-to-pixel-calculation. Experimental results on SPOT5 images are given to show the validity and advantages of the proposed approach.

关键词： change detection algorithms Image color analysis Remote sensing Pixel Image analysis Image segmentation Filters Morphology Image registration Cities and towns

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Quickest change detection in multiple on-off processes

Quickest change detection in multiple on-off processes

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qing Zhao Jia Ye University of California Davis CA USA

A Bayesian formulation of quickest change detection in multiple on-off processes is obtained within a decision-theoretic framework. For geometrically distributed busy and idle times, we show that the optimal joint design of channel switching and change detection has a simple threshold structure under a mild condition. Extensions to arbitrarily distributed busy and idle times, in particular, heavy tail distributions, are discussed. We show that this problem presents a fresh twist to the classic problem of quickest change detection that considers only one stochastic process. We demonstrate that the key to quickest change detection in multiple processes is to abandon the current process when its state is unlikely to change in the near future (as indicated by the measurements obtained so far) and seek opportunities in a new process to avoid realizations of long busy periods. This problem arises in spectrum opportunity detection in cognitive radio networks where a secondary user searches for idle channels in the spectrum.

关键词： Probability distribution Stochastic processes Bayesian methods Cognitive radio Current measurement Switches detection algorithms Exponential distribution change detection algorithms Telecommunication network reliability

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HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

HMM triangle relative entropy concepts in sequential change ...

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International Conference on Information Fusion

作者： Timothy L. Molloy Jason J. Ford School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane QLD Australia

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

关键词： Hidden Markov models Entropy Probabilistic logic detection algorithms change detection algorithms Density measurement Maximum likelihood estimation

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change detection based on graph cuts

Change detection based on graph cuts

引用

International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Alina Miron Atta Badii Intelligent Systems Research Laboratory University of Reading United Kingdom

In this paper we propose a moving object detection system based on Graph Cut. Our method relies on motion modelling using an optical flow algorithm and a classical background subtraction module based on Mixture of Gaussians. The main contribution in our approach is the fusion of the two mask models, as well as the particular cost function used by the Graph Cut algorithm. The experiments as performed on CDnet 2014 benchmark showed that our system has very good results in scenarios such as Bad Weather or PTZ, but is less robust in detecting small changes in the scene.

关键词： change detection algorithms Image color analysis Meteorology Conferences Heuristic algorithms Optical imaging Minimization

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A variational Bayesian approach to remote sensing image change detection

A variational Bayesian approach to remote sensing image chan...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Keming Chen Zhenglong Li Jian Cheng Zhixin Zhou Hanqing Lu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

In this paper, we present a variational Bayesian (VB) approach to multitemporal remote sensing image change detection. The content of the so called `difference image' is modeled by finite Gaussians Mixture Model (GMM), then with the factor analysis techniques, underlying structure of image content is inferred automatically. Compared with the Expectation-Maximization (EM) algorithm, the proposed method can adaptively determine the number of components in the mixture model without usual sub- or over-segmentation problem. Moreover, to overcome the local optimization problem, a component split strategy is employed in inference process. Experimental results confirm the effectiveness of the proposed method.

关键词： Bayesian methods Remote sensing Inference algorithms change detection algorithms Image analysis Iterative algorithms Gaussian processes Layout Maximum likelihood detection Maximum likelihood estimation

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