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检索条件"主题词=Mean Shift Algorithm"

共 120 条记录，以下是101-110 订阅

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An unsupervised method for quality assessment of despeckling: An evaluation on COSMO-SkyMed data

An unsupervised method for quality assessment of despeckling...

引用

Conference on SAR Image Analysis, Modeling, and Techniques XI

作者： Aiazzi, B. Alparone, L. Argenti, F. Baronti, S. Bianchi, T. Lapini, A. Ist Fis Appl Nello Carrara Area Ric Firenze I-50019 Sesto Fiorentino Italy Univ Florence Dipartimento Elettron & Telecomunicaz I-50139 Florence Italy

ISBN: (纸本)9780819488060

Goal of this paper is the development and evaluation of a fully automatic method for quality assessment of despeckled synthetic aperture radar (SAR) images. The rationale of the new approach is that any structural perturbation introduced by despeckling, e. g. a local bias of mean or the blur of a sharp edge or the suppression of a point target, may be regarded either as the introduction of a new structure or as the suppression of an existing one. Conversely, plain removal of random noise does not change structures in the image. Structures are identified as clusters in the scatterplot of original to filtered image. Ideal filtering should produce clusters all aligned along the main diagonal. In practice clusters are moved far from the diagonal. Clusters' centers are detected through the mean shift algorithm. A structural change feature is defined at each pixel from the position and population of off-diagonal cluster, according to Shannon's information theoretic concepts. Results on true SAR images (COSMO-SkyMed) will be presented. Bayesian estimators (LMMSE: liner minimum mean squared error: MAP: maximum alpha-posteriori probability) operating in the undecimated wavelet domain have been coupled with segment-based processing. Quality measurements of despeckled SAR images carried out by means of the proposed method highlight the benefits of segmented MAP filtering.

关键词： Clustering despeckling mean shift algorithm multivariate analysis quality measurements SAR imagery

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PATHOLOGY-ROBUSTMR INTENSITY NORMALIZATION WITH GLOBAL AND LOCAL CONSTRAINTS

PATHOLOGY-ROBUSTMR INTENSITY NORMALIZATION WITH GLOBAL AND L...

引用

8th IEEE International Symposium on Biomedical Imaging (ISBI) - From Nano to Macro

作者： Ekin, Ahmet Philips Res Video & Image Proc Grp Eindhoven Netherlands

ISBN: (纸本)9781424441280

The intensity values in magnetic resonance (MR) images are not standardized. This prevents intensity comparison of different MR volumes that may be needed for visualization, intensity-based processing, and diagnosis. To this effect, this paper introduces a novel, pathology-robust MR intensity normalization algorithm that improves over the literature in three major aspects: 1) Pathology robustness: We achieve this by comparing the input MR volume with a reference volume, identifying the modes of their joint intensity distribution by the mean shift algorithm, and assigning each voxel a confidence value based on the distance of its intensity to the nearby mode. 2) Global and local analysis: We improve both the global similarity of intensities by matching the input and the reference histograms with histogram specification, and the local intensity similarity by minimizing the mean voxel intensity difference with dynamic programming. 3) Structure-preserving fusion of global and local approaches: The optimal fusion of global and local metrics is achieved by preserving the structures (defined as edges) in the normalized data compared with those in the input. We show the effectiveness of the proposed method with both visual and quantitative results.

关键词： Dynamic programming Equations Histograms Joints MR imaging Magnetic resonance Pathology Table lookup biomedical MRI brain brain diseases dynamic programming dynamic programming global constraints global similarity histogram specification image fusion image registration image segmentation intensity normalization joint intensity distribution local constraints magnetic resonance mean shift algorithm mean voxel intensity difference medical image processing pathology robustness

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Visual Tracking by Adaptive Kalman Filtering and mean shift

引用

6th Hellenic Conference on Artificial Intelligence

作者： Karavasilis, Vasileios Nikou, Christophoros Likas, Aristidis Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece

ISBN: (纸本)9783642128417

A method for object tracking combining the accuracy of mean shift with the robustness to occlusion of Kalman filtering is proposed. At first, an estimation of the object's position is obtained by the mean shift tracking algorithm and it is treated as the observation for a. Kalman filter. Moreover, we propose a dynamic scheme for the Kalman filter as the elements of its state matrix are updated on-line depending on a measure evaluating the quality of the observation. According to this measure, if the target is not occluded the observation contributes to the update equations of the Kalman filter state matrix. Otherwise, the observation is not taken into consideration. Experimental results show significant improvement with respect to the standard mean shift method both in terms of accuracy and execution time.

关键词： Visual tracking Kalman filter mean shift algorithm

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mean shift algorithm and its application in tracking of objects

Mean shift algorithm and its application in tracking of obje...

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5th International Conference on Machine Learning and Cybernetics

作者： Wen, Zhi-Qiang Cai, Zi-Xing Cent South Univ Coll Informat Sci & Engn Changsha 410083 Peoples R China

ISBN: (纸本)1424400600

mean shift algorithm is recently widely used in tracking clustering, etc, however convergence of mean shift algorithm has not been rigorously proved. In this paper mean shift algorithm with Gaussian profile is studied and applied to tracking of objects. The imprecise proofs about convergence of mean shift are firstly pointed out. Then a convergence theorem and its rigorous convergence proof are provided. Lastly tracking approach of objects based on mean shift is modified. The results of experiment show the modified approach has good performance of object tracking applied to occlusion. The contributions in this paper are expected to further study and application in mean shift algorithm.

关键词： mean shift algorithm convergence kernel function tracking of object Bhattacharyya coefficient

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A Medical Tracking System for Contrast Media

A Medical Tracking System for Contrast Media

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International Conference on Life System Modeling and Simulation / International Conference on Intelligent Computing for Sustainable Energy and Environment (LSMS-ICSEE)

作者： Dai, Chuan Wang, Zhelong Zhao, Hongyu Dalian Univ Technol Fac Elect Informat & Elect Engn Dalian 116024 Peoples R China

ISBN: (纸本)9783642156144

Contrast media is a kind of chemical substance used to improve the image quality of Computed Tomography. However, due to its high speed of injection, emergencies (such as capillary hemorrhage) always exist. In view of this problem, a video object tracking system is implemented to monitor the injection site. The color feature is abstracted from image sequences and used for the mean shift tracking algorithm. The experiment results show that the tracking system is real-time, robust and efficient.

关键词： Tracking Visual tracking Color histogram mean shift algorithm

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Human face tracking with adaptive facial orientation template by mean shift algorithm

Human face tracking with adaptive facial orientation templat...

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8th International Conference on Signal Processing

作者： Wang, Yanjiang Liu, Baodi Wang, Wuli China Univ Petr Coll Informat & Control Engn Shandong 257061 Peoples R China

ISBN: (纸本)9780780397361

mean shift algorithm has been used in human face tracking during past years and exhibited robust performance compared with other methods. However the existed mean shift methods usually track faces with vertical orientation and the tracking effect is deteriorated when the facial orientation changed. In addition, it often adopts the color histogram in RGB color space, which is sensitive to lighting variations. In this paper, we present an adaptive facial orientation template for face tracking in YCb Cr color space and the experimental results show that the tracking is more efficient to adapt the facial orientation and lighting variations than current methods.

关键词： mean shift algorithm adaptive facial orientation template color histogram face tracking

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mean shift algorithm AND ITS APPLICATION IN TRACKING OF OBJECTS

MEAN SHIFT ALGORITHM AND ITS APPLICATION IN TRACKING OF OBJE...

引用

2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： ZHI-QIANG WEN ZI-XING CAI College of Information Science and Engineering Central South University HuNan Changsha 410083 China

mean shift algorithm is recently widely used in tracking clustering, etc, however convergence of mean shift algorithm has not been rigorously proved. In this paper mean shift algorithm with Gaussian profile is studied and applied to tracking of objects. The imprecise proofs about convergence of mean shift are firstly pointed out. Then a convergence theorem and its rigorous convergence proof are *** tracking approach of objects based on mean shift is modified. The results of experiment show the modified approach has good performance of object tracking applied to occlusion. The contributions in this paper are expected to further study and application in mean shift algorithm.

关键词： mean shift algorithm Convergence Kernel function Tracking of object Bhattacharyya coefficient

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A medical tracking system for contrast media

A medical tracking system for contrast media

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2010 International Conference on Life System Modeling and Simulation & 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment

作者： Chuan Dai, Zhelong Wang and Hongyu Zhao Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian, 116024.CHINA,

关键词： Tracking Visual tracking Color histogram mean shift algorithm

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An Adaptive Target Tracking algorithm based on Multi-feature Fusion

An Adaptive Target Tracking Algorithm based on Multi-feature...

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International Conference on Biomedical Engineering and Computer Science

作者： Shengzhi Yuan Jian hua Li Jianli Han Department of ordnance science and technology naval aeronautical and astronautical university Department of scientific research naval aeronautical and astronautical university

ISBN: (纸本)9781424453153;9781424453160

although widely used in practice for real time ability, the mean shift algorithm was weak at target model description and was robust for infrared image sequences form motion platform. In order to enhance the adaptability and target description ability of the mean shift algorithm, meanwhile to make up the shortcomings of the nuclear density estimation based on gradation feature, an adaptive Kalman-mean shift algorithm based on multi-feature fusion was proposed. A target description mode based on gradation-edge feature fusion was applied, while a scale updating item of tracking window was used in the mean shift algorithm based on the relation between mutual information and the object scale. Experimental results demonstrate that the adaptability of mean shift algorithm is enhanced by the improved algorithm, which is effectively applied in the tracking problem for the object of scale variance in long time tracking process.

关键词： Multi-feature fusion Target tracking mean shift algorithm Mutual information

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Region based Segmentation using Dual Tree Complex Wavelet Transform and Rotated Complex Wavelet Filter

Region based Segmentation using Dual Tree Complex Wavelet Tr...

引用

2009 Annual IEEE India Conference

作者： Phadke, Anuradha C. Wadke, Sonali R. Rege, Priti R. Maharashtra Inst Technol Elect & Telecommun Engg Dept Pune Maharashtra India Coll Engn Elect & Telecommun Engn Dept Pune Maharashtra India

ISBN: (纸本)9781424448586

In this paper, we have proposed a novel approach for segmentation of textured images using combination of Dual Tree Complex Wavelet Transform (DT-CWT) and Dual Tree Rotated complex Wavelet Filters (DT-RCWFs). DT-CWT is used because of its properties such as shift invariance, good directional selectivity, limited redundancy and efficient computation. RCWF sets provide important complementary information to the DT-CWT filter set by extracting texture features in 6 different directions which are 45(0) apart from decomposition directions of DT-CWT. mean shift algorithm is used along with fuzzy c-means (FCM) to make segmentation automatic. The proposed technique is tested on a range of textured images including composite texture images, synthetic texture images as well as real scene images.

关键词： DT-CWT RCWF Region based segmentation mean shift algorithm FCM

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