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检索条件"机构=Computer Vision Image Processing Laboratory"

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Shape-constraint for accurate segmentation in remote sensing imagery

Shape-constraint for accurate segmentation in remote sensing...

引用

International Conference on Information Fusion

作者： A. El-Baz R. Mohamed A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA

A new approach is proposed for the segmentation of remote sensing images which is based on using a prior shape information. This information is obtained from a set of signed distance functions (SDF). Each SDF represents the training data set as a histogram of the occurrences of the data points inside and outside a specific object. A statistical approach is proposed for modeling each SDF, which is considered to have a random distribution. The mean field theory-based support vector machines (MF-based SVM) density estimator is used to estimate the probability density function which underlies the random distribution of the SDF. The statistical modeling of shapes enables realistic representation of objects especially those which are not contiguous within the image; i.e., objects which consist of multiple regions. This modeling is used to substitute for the class priors in a Bayes segmentation setup, in which the class conditional probabilities are estimated using the MF-based SVM algorithm also. Experiments with multispectral remote sensing data show that the proposed segmentation approach is more accurate and robust than other known alternatives.

关键词： image segmentation Remote sensing Shape measurement Surface cleaning Support vector machines computer vision Pixel image processing Laboratories Training data

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A novel framework for N-D multimodal image segmentation using graph cuts

A novel framework for N-D multimodal image segmentation usin...

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IEEE International Conference on image processing

作者： Asem M. Ali Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA

This work proposes a new MAP-based segmentation framework of multimodal images. In this work a joint MGRF model is used to describe the image. The main focus here is a more accurate model identification. For a known number of classes in the given image, the empirical distributions of this image signals are precisely approximated by a LCG distributions with positive and negative components. Gibbs potential, which is used to identify the spatial interaction between the neighboring pixels, is analytically estimated. Finally, an energy function using the previous models is formulated and is globally minimized using graph cuts. Experiments show that the developed technique gives promising accurate results compared to other known algorithms.

关键词： image segmentation Pixel Joining processes Labeling image processing Gray-scale Robustness Object segmentation computer vision Laboratories

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Remote sensing image segmentation using SVM with automatic selection for the kernel parameters

Remote sensing image segmentation using SVM with automatic s...

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International Conference on Information Fusion

作者： R. Mohamed A. El-Baz A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA

The kernel function plays a basic role in support vector machines (SVM) algorithms. This paper presents an automatic method for selecting the parameters of the Gaussian radial basis function (GRBF) kernel which is one of the commonly used forms in SVM regression algorithms. The proposed method uses the expectation maximization (EM) algorithm for the automatic selection. The SVM regression algorithm is used to solve two major problems in remote sensing image segmentation: the density estimation problem and the Markov random field modeling problem. The density estimation is used for class conditional probabilities in Bayesian setups. The MRF is used for region modeling in boosting the Bayesian image segmentation. The proposed algorithms are integrated in a framework for remote sensing image segmentation. Experimental evaluation of the proposed algorithms using synthetic data set and hyperspectral data set illustrates the outstanding performance of the proposed algorithms.

关键词： Remote sensing image segmentation Support vector machines Kernel Probability Markov random fields Bayesian methods Covariance matrix computer vision image processing

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One-sided transparency: A novel visualization for tubular objects

One-sided transparency: A novel visualization for tubular ob...

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作者： Curtin, Robert Ismail, Marwa Farag, Aly Sites, Chuck Elshazly, Salwa Falk, Robert Computer Vision and Image Processing Laboratory University of Louisville LouisvilleKY United States Kentucky Imaging Technologies LouisvilleKY United States Medical Imaging Jewish Hospital Abraham Flexner Way Louisville United States

ISBN: (纸本)9781479957514

This paper describes a unique method for tubular object visualization. The method involves rendering the exterior of the tube invisible while keeping the interior visible. This 'One-sided-transparency' technique renders a more complete view of the tube's interior. When applied to virtual colonoscopy (VC), it compares favorably to existing methods. It provides more complete images, reduces computational time, and reduces memory requirements while preserving VCs benefits for patients and practitioners. The approach also has various potential uses outside of VC. © 2014 IEEE.

关键词： Transparency

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Fast recovery of piled deformable objects using superquadrics

Fast recovery of piled deformable objects using superquadric...

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24th German Association for Pattern Recognition Symposium, DAGM 2002

作者： Katsoulas, Dimitrios Jaklič, Aleš Institute for Pattern Recognition and Image Processing University of Freiburg Georges-Koehler-Allee 52 FreiburgD-79110 Germany Computer Vision Laboratory University of Ljubljana Tržaška cesta 25 LjubljanaSI-1000 Slovenia

ISBN: (纸本)354044209X

Fast robotic unloading of piled deformable box-like objects (e.g. box-like sacks), is undoubtedly of great importance to the industry. Existing systems although fast, can only deal with layered, neatly placed configurations of such objects. In this paper we discuss an approach which deals with both neatly placed and jumbled configurations of objects. We use a time of flight laser sensor mounted on the hand of a robot for data acquisition. Target objects are modeled with globally deformed superquadrics. Object vertices are detected and superquadric seeds are placed at these vertices. Seed refinement via region growing results in accurate object recovery. Our system exhibits a plethora of advantages the most important of which its speed. Experiments demonstrate that our system can be used for object unloading in real time, when a multi-processor computer is employed. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Data acquisition

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An investigation of JPEG image and video compression using parallel processing

An investigation of JPEG image and video compression using p...

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

作者： G.W. Cook E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The problem inherent with any digital image (or digital video) system is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop more complex algorithms that compress images to lower data rates with better fidelity. One approach that can be used to increase the execution speed of these complex algorithms is through the use of parallel processing. In this paper we address one aspect of the parallel implementation of the JPEG still image compression standard on the MasPar MP-1, a massively parallel SIMD computer. We develop a novel byte alignment algorithm used to efficiently output compressed data from the parallel system.< >

关键词： Transform coding Video compression Parallel processing image coding image storage Digital images Concurrent computing Parallel algorithms image processing Bandwidth

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Optimal surface normal from affine transformation 10

Optimal surface normal from affine transformation

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10th International Conference on computer vision Theory and Applications, VISAPP 2015

作者： Daniel, Barath Molnar, Jozsef Hajder, Levente Geometric Modelling and Computer Vision Laboratory MTA SZTAKI Kende utca 13-17 BudapestH-1111 Hungary Department of Image Processing and Computer Graphics Institute of Informatics University of Szeged Árpád tér 2 SzegedH-6720 Hungary

ISBN: (纸本)9789897580918

This paper deals with surface normal estimation from calibrated stereo images. We show here how the affine transformation between two projections defines the surface normal of a 3D planar patch. We give a formula that describes the relationship of surface normals, camera projections, and affine transformations. This formula is general since it works for every kind of cameras. We propose novel methods for estimating the normal of a surface patch if the affine transformation is known between two perspective images. We show here that the normal vector can be optimally estimated if the projective depth of the patch is known. Other non-optimal methods are also introduced for the problem. The proposed methods are tested both on synthesized data and images of real-world 3D objects.

关键词： Cameras

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Rapid shallow coastal coral reef mapping using the teardrop system

Rapid shallow coastal coral reef mapping using the teardrop ...

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OCEANS 2012 MTS/IEEE Hampton Roads Conference: Harnessing the Power of the Ocean

作者： Corpuz, Francis James Naval Jr., Prospero Capili, Eusebio Jauod, Jaylord Judilla, Roel John Soriano, Maricor Vision and Image Processing Group National Institute of Physics University of the Philippines Diliman Quezon City Philippines Computer Vision and Machine Intelligence Group Department of Computer Science University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Institutional Laboratory Mgmt Office Mapua Institute of Technology Intramuros Manila Philippines

ISBN: (纸本)9781467308298

We present a rapid shallow coastal reef mapping system using a previously developed inexpensive diver less video capture system coupled with a fast-image mosaicking technique, using an affordable GPS logging device. The system replaces the traditional manta tow system of assessing and monitoring large areas of coastal coral reefs and at the same time provides historical visual record for future references. The system utilizes Teardrop, a hollow, teardrop-shaped that houses a commercial underwater point-and-shoot camera. The camera is set to video mode and captures video of the reef while the Teardrop is being towed by a wooden fishing boat. The resulting video is parsed into frames and mosaicked by using fast image labeling. The approximate location of the mosaicked images is recorded by using an inexpensive GPS logger. The coordinates are embedded on the mosaicked images and overlaid on mapping software such as Google Earth for visual record and spatial information integration. The same points are used to compute for the total distance covered by the capturing process. The whole process from coral reef video capture to mosaicking the images and finally embedding the mosaics in mapping software can be done in as short as 1 day, providing coastal managers and local government units with a tool to rapidly visualize and monitor shallow coral reefs. © 2012 IEEE.

关键词： Mapping

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Multi-modal medical volumes fusion by surface matching

Multi-modal medical volumes fusion by surface matching

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International Symposium on Signal processing and Its Applications (ISSPA)

作者： A.M. Eldeib S.M. Yamany A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

Presents a fast, six degrees of freedom, registration technique to accurately locate the position and orientation of medical volumes (e.g. CT, MRI) with respect to each other for the same patient. The technique uses surface registration and maximization of mutual information. We have developed a novel technique for surface registration which produces highly accurate results when registering two different volumes of the same individual generated from the same modality, such as preoperative MR and intraoperative MR volumes. In case surface registration is not able to accurately register the different volumes, the result is enhanced by multi-modal volume registration. The gain of this combination is to have an accurate alignment and to reduce time needed for registration. For the multi-modal volume registration, the maximization of mutual information (MI) as a matching criterion is used based on genetic algorithms (GA) as a search engine. Our results demonstrate that our registration technique allows for fast, accurate, robust and completely automatic registration of multimodality medical volumes.

关键词： Biomedical imaging Medical diagnostic imaging Computed tomography Mutual information Magnetic resonance imaging Data mining Magnetic resonance Genetic algorithms Shape computer vision

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Free-form surface registration using surface signatures

Free-form surface registration using surface signatures

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International Conference on computer vision (ICCV)

作者： S.M. Yamany A.A. Farag Computer Vision and Image Processing Laboratory Electrical Engineering Department University of Louisville Louisville KY USA

The paper introduces a new free-form surface representation scheme for the purpose of fast and accurate registration and matching. Accurate registration of surfaces is a common task in computer vision. The proposed representation scheme captures the surface curvature information seen from certain points and produces images called surface signatures at these points. Matching signatures of different surfaces enables the recovery of the transformation parameters between these surfaces. We propose to use template matching to compare the signature images. To enable partial matching, another criterion, the overlap ratio, is used. This representation scheme can be used as a global representation of the surface as well as a local one and performs near real time registration. We show that the signature representation can be used to match objects in 3D scenes in the presence of clutter and occlusion. Applications presented include free-form object matching, multimodal medical volume registration and dental teeth reconstruction from intra-oral images.

关键词： Shape computer vision Surface reconstruction Application software Biomedical imaging image processing Layout Dentistry Teeth image reconstruction

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