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Conference on Wavelet Applications in Signal and Image Processing VIII

作者： Do, MN Lozano, AC Vetterli, M Swiss Fed Inst Technol Lab Audiovisual Commun CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

A new statistical model for characterizing texture images based on wavelet-domain hidden Markov models and steerable pyramids is presented. The new model is shown to capture well both the subband marginal distributions and the dependencies across scales and orientations of the wavelet descriptors. Once it is trained for an input texture image, the model can be easily steered to characterize that texture at any other orientations. After a diagonalization operation, one obtains a rotation-invariant description of the texture image. The effectiveness of the new model is demonstrated in large test image databases where significant gains in retrieval performance are shown.

关键词： Wavelets Databases Data modeling Matrices Image retrieval expectation maximization algorithms Statistical analysis Wavelet transforms Statistical modeling Feature extraction

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POSSIBILITIES OF THE FRINGE PATTERN LEARNING-SYSTEM VARNA

POSSIBILITIES OF THE FRINGE PATTERN LEARNING-SYSTEM VARNA

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CONF ON HOLOGRAPHY, INTERFEROMETRY, AND OPTICAL PATTERN RECOGNITION IN BIOMEDICINE

作者： NEDKOVA, R Central Lab. of Optical Storage and Processing of Informatio (Bulgaria)

The possibilities of this learning system made for interferogram and speckle-correlogram processing are reviewed. Its easy learning and robustness seem to be useful both for industrial applications and for experiment.

ISBN: (纸本)0819405191

关键词： Fringe analysis Bismuth Computing systems Holography Interferometry Logic Optical pattern recognition Speckle expectation maximization algorithms Neodymium

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Intrusion detection for internet of things security: a hidden markov model based on fuzzy rough set 4

Intrusion detection for internet of things security: a hidde...

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4th International Conference on Green Communication, Network, and Internet of Things, CNIoT 2024

作者： Wang, Yuanting Wu, Guoliang Inner Mongolia Electric Power Co. Ltd. Baotou Power Supply Company Baotou China

ISBN: (纸本)9781510685710

Internet of Things (IoT) devices are vulnerable to various cyber-attacks. Therefore, it is significantly crucial to design an effective intrusion detection system (IDS) for IoT security. However, IoT devices have limited resources such as computing resources needing to handle a great of data, which further increases the difficulty of precise intrusion detection. Moreover, most IDSs lack transparency. This study develops a feature selection-based hidden Markov model (HMM) for intrusion detection. We first establish a modified approach based on a fuzzy rough set for feature selection to select optimal features so that the computational burden can be reduced. Furthermore, an interpretable intrusion detection model is established based on the HMM. In addition, intrusion detection is achieved in the presence of partially missing data through the expectation-maximization algorithm. According to the simulation results, the proposed method is able to detect intrusion detection in IoT networks effectively. © 2024 SPIE.

关键词： Internet of things Computer intrusion detection expectation maximization algorithms Data modeling Cyberattacks Fuzzy logic Network security Feature extraction Chromium Education and training

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UNIFIED STOCHASTIC IMAGE MODEL AND UNSUPERVISED IMAGE-ANALYSIS TECHNIQUE FOR NONDIFFRACTION CT IMAGING

UNIFIED STOCHASTIC IMAGE MODEL AND UNSUPERVISED IMAGE-ANALYS...

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CONF ON APPLICATIONS OF DIGITAL IMAGE PROCESSING 13

作者： DAI, J LEI, TH SEWCHAND, W Univ. of Maryland (United States) Univ. of Maryland School of Medicine (United States) Univ. of Maryland School of Me (United States)

This paper briefly describes the stochastic image model and the image analysis technique for X-ray CT, and then validates the use of this model and technique to MRI modality. The results of image analysis from the use... 详细信息

ISBN: (纸本)0819404101

关键词： Image segmentation X-ray computed tomography Image analysis Digital image processing X-rays expectation maximization algorithms X-ray imaging Magnetic resonance imaging Stochastic processes Image processing

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Analysis of brain images using the 3D-CSC segmentation method

Analysis of brain images using the 3D-CSC segmentation metho...

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Medical Imaging 2006 Conference

作者： Priese, Lutz Schmitt, Frank Sturm, Patrick Wang, Haojun Matern, Ralf Wickenhoefer, Ralph Univ Koblenz Landau Inst Comp Visualist Koblenz Germany GAFCH Koblenz Germany

ISBN: (纸本)0819464236

The 2D segmentation method CSC (Color Structure Code) for color images has recently been generalized to 3D color or grey valued images. To apply this technique for an automated analysis of 3D MR brain images a few preprocessing and postprocessing steps have been added. We present this new brain analysis technique and compare it with SPM.

关键词： Image segmentation Brain Neuroimaging Scanning probe microscopy 3D image processing Magnetic resonance imaging Image analysis Visualization Bridges expectation maximization algorithms

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Spatial modeling of occlusion patterns applied to the detection of surface-laid mines

Spatial modeling of occlusion patterns applied to the detect...

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Conference on Detection and Remediation Technologies for Mines and Minelike Targets IX

作者： Lundberg, M Brown, CL Uppsäll, M Lulea Univ Technol Div Signal Proc S-95187 Lulea Sweden

ISBN: (纸本)0819453382

Images recorded in ground areas potentially containing surface laid land mines are considered. The first hypothesis is that the image is of clutter (grass) only, while the alternative is that the image contains a partially occluded (covered) land mine in addition to the clutter. In such a scenario, the occlusion pattern is unknown and has to be treated as a nuisance parameter. In a previous paper it was shown that deterministic treatment of the unknown occlusion pattern, in companion with the applied model, renders a substantial increase in detector performance as compared to employment of the traditional additive model. However, a deterministic assumption ignores possible correlation and additional gains could be possible by taking the spatial properties into account. In order to incorporate knowledge regarding the occlusion, the spatial distribution is characterized in terms of an underlying Markov Random Field (MRF) model. A major concern with MRF models is their complexity. Therefore, in addition to this, a less computationally demanding technique to accommodate the occlusion behavior is also proposed. The main purpose of this paper is to investigate if significant gains are possible by acknowledging the spatial dependence. Evaluation on data using real occluded targets however indicates that the gain seem to be marginal.

关键词： Land mines Mining Magnetorheological finishing Digital filtering Sensors Image filtering expectation maximization algorithms Electro optical modeling Performance modeling Target detection

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Biologically inspired feature based categorization of objects.

Biologically inspired feature based categorization of object...

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Conference on Human Vision and Electronic Imaging IX

作者： Mundhenk, TN Navalpakkam, V Makaliwe, H Vasudevan, S Itti, L Univ So Calif Dept Comp Sci Henry Salvatori Comp Sci Ctr Los Angeles CA 90089 USA

ISBN: (纸本)0819451959

We have developed a method for clustering features into objects by taking those features which include intensity, orientations and colors from the most salient points in an image as determined by our biologically motivated saliency program. We can train a program to cluster these features by only supplying as training input the number of objects that should appear in an image. We do this by clustering from a technique that involves linking nodes in a minimum spanning tree by not only distance, but by a density metric as well. We can then form classes over objects or object segmentation in a novel validation set by training over a set of seven soft and hard parameters. We discus as well the uses of such a flexible method in landmark based navigation since a robot using such a method may have a better ability to generalize over the features and objects.

关键词： Algorithm development Image segmentation Independent component analysis Visualization Feature extraction Cameras Detection and tracking algorithms expectation maximization algorithms Navigation systems Object recognition

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Local color transfer between images using dominant colors

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JOURNAL OF ELECTRONIC IMAGING 2013年第3期22卷 033003-033003页

作者： Yoo, Jae-Doug Park, Min-Ki Cho, Ji-Ho Lee, Kwan H. Gwangju Inst Sci & Technol Kwangju 500712 South Korea Vienna Univ Technol A-1040 Vienna Austria

A color-transfer method that can transfer colors of an image to another for the local regions using their dominant colors is proposed. In order to naturally transfer the colors and moods of a target image to a source image, we need to find the local regions of colors that need to be modified in the image. Since the dominant colors of each image can be used for the estimation of color regions, we develop a grid-based mode detection, which can efficiently estimate dominant colors of an image. Based on these dominant colors, our proposed method performs a consistent segmentation of source and target images by using the cost-volume filtering. Through the segmentation procedure, we can estimate complex color characteristics and transfer colors to the local regions of an image. For an intuitive and natural color transfer, region matching is also crucial. Therefore, we use the visually prominent colors in the image to meaningfully connect each segmented region in which modified color-transfer method is applied to balance the overall luminance of the final result. In the Experimental Result section, various convincing results are demonstrated through the proposed method. (C) 2013 SPIE and IS&T

关键词： algorithms Image processing Image segmentation Multilayers Color difference Digital imaging Matrices expectation maximization algorithms Human vision and color perception Data storage Principal component analysis Software MATLAB

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