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

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Stochastic deformable model

Stochastic deformable model

引用

2005 16th British Machine vision Conference, BMVC 2005

作者： El-Baz, Ayman Farag, Aly Gimelfarb, Georgy Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Department of Computer Science Tamaki Campus University of Auckland Auckland New Zealand

ISBN: (纸本)1901725294

Deformable or active contour, and surface models are powerful image segmentation techniques. We introduce a novel fast and robust bi-directional parametric deformable model which is able to segment regions of intricate shape in multi-modal greyscale images. The power of the algorithm in terms of computation time and robustness is owing to the use of joint probabilities of the signals and region labels in individual points as external forces guiding the model evolution. These joint probabilities are derived from a Markov-Gibbs random field (MGRF) image model considering an image as a sample of two interrelated spatial stochastic processes. The low level process with conditionally independent and arbitrarily distributed signals relates to the observed image whereas its hidden map of regions is represented with the high level MGRF of interdependent region labels. Marginal probability distributions of signals in each region are recovered from a mixed empirical signal distribution over the whole image. In so doing, each marginal is approximated with a linear combination of Gaussians (LCG) having both positive and negative components. The LCG parameters are estimated using our previously proposed modification of the EM algorithm, and the high-level Gibbs potentials are computed analytically. Comparative experiments show that the proposed model outlines complicated boundaries of different modal objects much more accurately than other known counterparts.

关键词： Random processes

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Robust robotic path planning using level sets

Robust robotic path planning using level sets

引用

IEEE International Conference on image processing

作者： M.S. Hassouna A.E. Abdel-Hakim A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY

In this paper, we propose a general and robust robotic path planning framework for both planar and terrain environments using level set methods. The framework is general in the sense that it can be used for both 2D and 3D environments. It generates a collision-free optimum paths for the entire or a portion of the configuration space. The optimum planned path can be controlled to follow the safest, shortest, or hybrid path. We have demonstrated the robustness of the proposed framework by correctly extracting all planned paths of complex maps with several obstacles.

关键词： Robustness Path planning Orbital robotics Navigation Level set Robot sensing systems Topology computer vision image processing Laboratories

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A clique of active appearance models by minimum description length

A clique of active appearance models by minimum description ...

引用

2005 16th British Machine vision Conference, BMVC 2005

作者： Langs, Georg Peloschek, Philipp Donner, René Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Department of Diagnostic Radiology Medical University of Vienna Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria

ISBN: (纸本)1901725294

Autonomous model building is a crucial trend in model based methods like AAMs. This paper introduces an approach that deals with non-linearities by detecting distinct sub-parts in the data. Sub-models each representing an individual sub-part are derived from a minimum description length criterion. Thereby the resulting clique of models is more compact and obtains a better generalization behavior than a single model. The proposed AAM clique generation deals with non-linearities in the data in a generic information theoretic manner reducing the necessity of user interaction during training.

关键词： Information theory

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Virtual Forces for Camera Planning in Smart vision Systems

Virtual Forces for Camera Planning in Smart Vision Systems

引用

IEEE Workshop on Applications of computer vision (WACV)

作者： Aly A. Farag Alaa E. Abdel-Hakim Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

In this paper, we present a novel and robust approach for camera planning in smart vision systems. The proposed approach uses virtual forces to adjust the camera parameters (pan, tilt, translation ... etc.) toward the most proper values with respect to the application. It employs the physical spring model to direct the motion of the camera toward its target. Our approach is a general framework and any vision system can be easily modeled to use it. This approach has several advantages over previous work in camera planning. It is portable, expandable, robust, and flexible. We present a case study of a two degree-of-freedom stereo vision system to test our approach. The results show the efficiency of our approach even with poor system initialization and its robustness against possible weakness in the auxiliary algorithms used.

关键词： Smart cameras Machine vision Process planning Robustness Sensor systems Sensor phenomena and characterization Application software computer vision Springs System testing

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PDE-based robust robotic navigation

PDE-based robust robotic navigation

引用

Canadian Conference on computer and Robot vision, CRV

作者： M.S. Hassouna A.E. Abdel-Hakim A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

In this paper, we propose a general, robust, and fast path planning framework for robotic navigation using level set methods. A medial point of the map is selected automatically to be a point source that transmits two wave fronts of different speeds. The first front propagates with a moderate speed to capture the map topology, while the second one propagates much faster at medial points such that the safest paths intersect the propagating fronts at those points of maximum positive curvature, which are identified by solving an ordinary differential equation (ODE). The motion of the front is governed by a nonlinear partial differential equation (PDE), which is efficiently solved using robust level set methods. The framework is general in the sense that it can be used for both 2D and 3D environments. It generates a collision-free optimum paths for partial or complete configuration space. Optimum planned paths can be controlled according to the surrounding environment and running conditions in order to follow the safest, shortest, or hybrid paths. We demonstrate the robustness of the proposed method by correctly extracting planned paths of complex maps with several obstacles.

关键词： Robustness Navigation Path planning Orbital robotics Robot vision systems Level set computer vision Topology image processing Laboratories

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Vessel segmentation in angiograms using hysteresis thresholding

Vessel segmentation in angiograms using hysteresis threshold...

引用

9th IAPR Conference on Machine vision Applications, MVA 2005

作者： Condurache, Alexandru-Paul Aach, Til Institute for Signal Processing University of Luebeck Ratzeburger Allee 160 D-23538 Luebeck Germany Institute of Image Processingand Computer Vision RWTH Aachen University Templergraben 55 D-52056 Aachen Germany

ISBN: (纸本)4901122045

Angiography (i.e. vessel imaging after the injection of a radiopaque substance) is a widely used procedure for vessel observation in both clinical routine and medical research. Often for the subsequent analysis of the vasculature it is needed to measure the angiogram area covered by vessels and/or the vessel length. For this purpose we need vessel enhancement and segmentation. While there are already many organ specific vessel segmentation algorithms, we propose in this contribution a more general method which includes a Hessian supported vessel enhancement step followed by segmentation based on the hysteresis threshold paradigm. Copyright © 2005 by MVA Conference Committee.

关键词： Hysteresis

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A silhouette-contour based 3-D registration methodology as a pre-evaluation step of 3-D reconstruction techniques

A silhouette-contour based 3-D registration methodology as a...

引用

IEEE International Conference on image processing

作者： A. Farag A. Eid Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY USA

Data registration is a crucial step in performance evaluation procedures that aim at localizing errors in given measured data. Under the performance evaluation topic, the probably corrupted measured data should be accurately registered/aligned to the ground truth data such that the registration process would not affect the accuracy of the consequent evaluation steps. To cope with this problem, another registration methodology that can go beyond the conventional ones should be used. Here we propose a novel approach for 3-D data registration. The performance of the approach is totally independent of the measured data set. The key advantage of this approach is that it keeps the registration process away from being affected by the probably corrupted data sets, hence it permits confidential evaluation results.

关键词： Three dimensional displays computer vision Iterative closest point algorithm Application software Iterative algorithms Calibration image processing Laboratories computer errors Object recognition

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Robust centerline extraction framework using level sets

Robust centerline extraction framework using level sets

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： M.S. Hassouna A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

In this paper, we present a novel framework for computing centerlines for both 2D and 3D shape analysis. The framework works as follows: an object centerline point is selected automatically as the point of global maximum Euclidean distance from the boundary, and is considered a point source (Ps) that transmits a wave front that evolves over time and traverses the object domain. The front propagates at each object point with a speed that is proportional to its Euclidean distance from the boundary. The motion of the front is governed by a nonlinear partial differential equation whose solution is computed efficiently using level set methods. Initially, the P/sub S/ transmits a moderate speed wave to explore the object domain and extract its topological information such as merging and extreme points. Then, it transmits a new front that is much faster at centerline points than non central ones. As a consequence, centerlines intersect the propagating fronts at those points of maximum positive curvature. Centerlines are computed by tracking them, starting from each topological point until the Ps is reached, by solving an ordinary differential equation using an efficient numerical scheme. The proposed method is computationally inexpensive, handles efficiently objects with complex topology, and computes centerlines that are centered, connected, one point thick, and less sensitive to boundary noise. In addition, the extracted paths form a tree graph without additional cost. We have extensively validated the robustness of the proposed method both quantitatively and qualitatively against several 2D and 3D shapes.

关键词： Robustness Level set Shape Euclidean distance Partial differential equations Data mining Merging Differential equations Topology Noise shaping

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Robust skeletonization using the fast marching method

Robust skeletonization using the fast marching method

引用

IEEE International Conference on image processing

作者： M.S. Hassouna A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

We have recently developed a level set based-framework for computing medial curves or curve skeletons CS for arbitrary 2D shapes as well as tubular and articulated 3D objects. The proposed framework is robust, fully automatic, computationally efficient, and produces curve skeletons that are connected, centered, thin, and less sensitive to boundary noise. In this paper, we introduce two improvements to the framework in order to enhance its performance in terms of stability and topology preserving.

关键词： Robustness Skeleton Shape Topology Cost function Level set Stability Partial differential equations computer vision image processing

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Stochastic segmentation of blood vessels from time-of-flight

Stochastic segmentation of blood vessels from time-of-flight

引用

IEEE International Conference on image processing

作者： M.S. Hassouna A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

In this paper, we present an automatic statistical approach for extracting 3D blood vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the dataset are classified as either blood vessels or background noise. The observed volume data is modeled by two stochastic processes. The low level process characterizes the intensity distribution of the data across the volume, while the high level process characterizes the statistical dependence among neighboring voxels. 3D Markov random field (MRF) has been employed to model the high level process, whose parameters are estimated using the maximum pseudo likelihood estimator (MPLE). Our proposed model exhibits a good fit to the clinical data and is extensively tested on different synthetic vessel phantoms and several TOF datasets. Experimental results showed that the proposed model is capable of delineating vessels down to 3 voxel diameters.

关键词： Stochastic processes Blood vessels Stochastic resonance Data mining Magnetic resonance Angiography Background noise Markov random fields Parameter estimation Testing

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