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IEEE International Conference on image processing

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

In this paper, we present a sensor planning approach for a mobile trinocular active vision system. At the stationary state (i.e., no motion) the sensor planning system calculates the generalized cameras' parameters (i.e., translational distance from the center, zoom, focus and vergence) using deterministic geometric specifications of both the sensors and the objects in their field of view. Some of these geometric parameters are difficult to be predetermined for the mobile system operation. In this paper, a new sensor planning approach, based on processing the content of the captured images, is proposed. The approach uses a combination of a closed-form solution for the translation between the three cameras, the vergence angle of the cameras as well as zoom and focus settings with the results of the correspondences between the acquired images and a predefined target object(s) obtained using the SIFT algorithm. We demonstrate the accuracy of the new approach using practical experiments.

关键词： image sensors Sensor systems Machine vision Cameras Focusing image reconstruction Robot sensing systems Robot vision systems Object detection Process planning

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A Unified Framework for Performance Evaluation of 3-D Reconstruction Techniques

A Unified Framework for Performance Evaluation of 3-D Recons...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

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

In this paper we consider the problem of performance evaluation of 3-D reconstruction techniques from calibrated sequence of images. We propose a unified framework for the evaluation process assuming the existence of ground truth data collected by a 3-D laser scanner. Firstly, we propose a new pre-evaluation technique for 3-D data registration based on silhouettes alignment. The performance of this technique is independent of the output quality of the 3-D reconstruction technique under test. This is a major advantage of our technique since the quality issue, which is not guarantee under the evaluation topic, is a challenge for any 3-D registration technique. Secondly, we propose a geometrically based evaluation methodology. The method is based on the geometrical matching of uniformly distributed patches of both ground truth and under-test data sets. The method is insensitive to the relative density of data sets. In addition, it provides a method for localizing errors which is a crucial step for diagnosis and data fusion post-evaluation techniques. Finally, we provide experimental results on the evaluation of stereo and space carving techniques.

关键词： Three dimensional displays Stereo vision Testing computer vision Optical sensors Cameras image processing Laboratories Stereo image processing Fuses

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Real-time vision-based approach for probe tracking in operating room

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International Congress Series 2004年 1268卷 467-472页

作者： Aly A. Farag M.Sabry Hassouna Ayman El-Baz S. Hushek Computer Vision and Image Processing Laboratory Electrical and Computer Engineering University of Louisville 403 Lutz Hall Bldg. Louisville KY 40292 USA Department of Neurological Surgery University of Louisville USA

A hand-held surgical probe is an essential component of any image-guided neurosurgery (IGNS). During the surgical procedure, the IGNS tracks the probe position and displays the anatomy beneath it as three orthogonal image slices on a workstation-based 3D imaging system. Existing IGNS systems use different tracking techniques including mechanical, optical, ultrasonic, and electromagnetic systems. In this paper, we present a new computational vision-based probe tracking technique, which provides both position and orientation. We also propose another new computational vision-based technique to track the patient head and thus compensate for its movement during probing procedure. The proposed system is completely passive, its stereo cameras detect the presence of the probe using available visible light, and reports on their exact location and orientation in patient physical space in real time. We have validated the system using a skull phantom and a hand made probe.

关键词： image-guided neurosurgery Head motion tracking Probe tracking vision tracking

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Automatic detection and recognition of lung abnormalities in helical CT images using deformable templates

Automatic detection and recognition of lung abnormalities in...

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Medical image Computing and computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings

作者： Farag, Aly El-Baz, Ayman Gimel'Farb, Georgy G. Falk, Robert Hushek, Stephen G. 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 Medical Imaging Division Jewish Hospital Louisville KY United States iMRI Department Norton Hospital Louisville KY United States

ISBN: (纸本)3540229779

Automatic detection of lung nodules is an important problem in computer analysis of chest radiographs. In this paper we propose a novel algorithm for isolating lung nodules from spiral CT scans. The proposed algorithm is based on using four different types of deformable templates describing typical geometry and gray level distribution of lung nodules. These four types are (z) solid spherical model of large-size calcified and non-calcified nodules appearing in several successive slices;(ii) hollow spherical model of large lung cavity nodules;(Hi) circular model of small nodules appearing in only a single slice;and (iv) semicircular model of lung wall nodules. Each template has a specific gray level pattern which is analytically estimated in order to fit the available empirical data. The detection combines the normalized cross-correlation template matching by genetic optimization and Bayesian post-classification. This approach allows for isolating abnormalities which spread over several adjacent CT slices. Experiments with 200 patients' CT scans show that the developed techniques detect lung nodules more accurately than other known algorithms. © Springer-Verlag Berlin Heidelberg 2004.

关键词： computer vision

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Enhancement of stents using interference of low-frequency ultrasonic echo signals

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Journal of Medical Ultrasonics 2004年第2期31卷 67-73页

作者： Ohashi, Gosuke Ohya, Akihisa Tobise, Kazimobu Akiyama, Iwaki Faculty of Engineering Shizuoka University Hamamatsu Japan Institute of Information Sciences and Electronics University of Tsukuba Tsukuba Japan Shoryo Electronic Corporation Kamakura Japan Faculty of Engineering Shonan Institute of Technology Fujisawa Japan Image Processing and Vision Research Laboratory Department of Electrical and Computer Engineering University of California at Santa Barbara Santa Barbara CA 93106-9560 United States

Purpose. We set out to enhance the imaging of stents used for coronary coarctation surgery without imaging the reticulation of the stent. Because the stent is a reticulated structure, there is a relation between ultrasound wavelength and the interstice reticulation that produces the echo. Methods. First we performed computer simulation by ultrasound frequency of transmitted signals to analyze this relation. Then, instead of controlling the transmitted wave, we processed the returned signals through a band-pass filter because of the difficulty of controlling the transmitted waves of diagnostic ultrasound equipment. Following this, we conducted experiments on an agar gel phantom containing a stent to verify the effectiveness of this method. Results. The simulation confirmed that the stent was apparent when the ultrasonic wavelength equaled the product of an integer and twice the interval of the reticulation of the stent. Application of a band-pass filter of 0.8 to 1.5MHz to the waveform returned from the agar gel phantom containing the stent. Conclusions. The effectiveness of this method in depicting the stent was confirmed. © The Japan Society of Ultrasonics in Medicine 2004.

关键词： Interference Received waveform Signal processing Stent Ultrasonic echography

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Multimodality image registration and fusion using neural network

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Journal of Harbin Institute of Technology(New Series) 2003年第3期10卷 235-240页

作者： Mostafa G Mostafa Aly A Farag Edward Essock Computer Vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USAComputer Vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USADept. of Psychology University of Louisville Louisville kY 40292 USA

Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.

关键词： data fusion image registration image interpolation neural network, 3-D model building

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Cerebrovascular segmentation for MRA data using level sets

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International Congress Series 2003年第C期1256卷 246-252页

作者： Hassan, Hossam Farag, Aly A Computer Vision Image Processing Laboratory University of Louisville Lutz Hall Louisville KY 40292 United States

In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Phase Contrast Magnetic Resonance Angiography, “PCMRA”. Classification model finds an optimal partition of homogeneous classes with regular interfaces. Regions and their interfaces are represented by level set functions. The algorithm initializes level sets in each image slice using automatic seed initialization and then iteratively, each level set approaches the steady state and contains the vessel or non-vessel area. The results are validated using a phantom that simulates the “PCMRA”. The approach is fast and accurate. Results on various cases demonstrate the accuracy of the approach. © 2003, Elsevier Science B.V. All rights reserved.

关键词： Level set segmentation PCMRA PDE Seed initialization Vascular tree

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Parameter estimation in Gibbs-Markov image models

Parameter estimation in Gibbs-Markov image models

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6th International Conference on Information Fusion, FUSION 2003

作者： El-Baz, Ayman Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184449

This paper introduces two novel approaches to estimate the clique potentials in binary and multilevel realizations of Gibbs Markov random field (GMRF) models. The first approach employs a genetic algorithm (CA) in order to arrive at the closest synthesized image that resembles the original "observed" image. The Second approach is used to estimate the parameters of Gaussian Markov random field. Given an image formed of a number of classes, an initial class density is assumed and the parameters of the densities are estimated using the EM approach. Convergence to the true distribution is tested using the Levy distance. The segmentation of classes is performed iteratively using the ICM algorithm and a genetic algorithm (GA) search approach that provides the maximum a posteriori probability of pixel classification. During the iterations, the GA approach is used to select the clique potentials of the Gibbs-Markov models used for the observed image. The algorithm stops when a fitness function, equivalent to the maximum a posteriori probability, does not change. The approach has been tested on synthetic and real images and is shown to provide satisfactory results. © Commonwealth of Australia 2003.

关键词： Genetic algorithms

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Two Sequential Stages Classifier for Multispectral Data

Two Sequential Stages Classifier for Multispectral Data

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Conference on computer vision and Pattern Recognition Workshop, CVPRW 2003

作者： Mohamed, Refaat M. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville LouisvilleKY40292 United States

ISBN: (纸本)0769519008

In this paper, we present an approach for the classification of remote sensing multispectral data, which consists of two sequential stages. The first stage exploits the capabilities of the Support Vector Machines (SVM) approach for density estimation and uses it in a Bayes classification setup. In a typical image, the class of a pixel is highly dependent on the classes of its neighbor pixels. The second stage exploits the dependency of the classes. We incorporate this dependency using stochastic modeling of the context as a Markov Random Field (MRF). The MRF is modeled using Besag model and implemented using the Iterative Conditional Modes (ICM) algorithm. Results show that the stochastic modeling approach enhances the results and provides reasonable smoothness in the classified image. © 2003 IEEE.

关键词： Remote sensing

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A new unsupervised approach for the classification of multispectral data

A new unsupervised approach for the classification of multis...

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6th International Conference on Information Fusion, FUSION 2003

作者： Mohamed, Refaat M. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184449

In this paper, we present a new approach for unsupervised pixel-wise classification of multispectral data. In this approach, we estimate the number of classes in a data set as well as the parameters of each class. This approach doesn't require training samples. A scene is modeled as a realization of a random field formed of a mixture distribution. We employ an EM algorithm to estimate the parameters of this mixture. The algorithm iterates to estimate the proper number of classes that compose the scene, and also the parameters of these classes. Theoretically, the algorithm can be applied for arbitrary forms of distributions for the classes in the scene, either parametric or non parametric. This paper focuses on the parametric estimation case. The approach has been applied to synthetic and real world multispectral data and provided quite encouraging results compared to other classical classification approaches. © Commonwealth of Australia 2003.

关键词： Classification (of information)

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