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IEEE International Conference on Image Processing

作者： Dong Wei B.L. Evans A.C. Bovik Laboratory for Vision Systems Department of Electrical and Computer Engineering University of Technology Austin TX USA

We define and construct a new family of compactly supported, nonseparable two-dimensional wavelets, "biorthogonal quincunx Coifman wavelets" (BQCWs), from their one-dimensional counterparts using the McClellan transformation. The resulting filter banks possess many interesting properties such as perfect reconstruction, vanishing moments, symmetry, diamond-shaped passbands, and dyadic fractional filter coefficients. We derive explicit formulas for the frequency responses of these filter banks. Both the analysis and synthesis lowpass filters converge to an ideal diamond-shaped halfband lowpass filter as the order of the corresponding BQCW system tends to infinity. Hence, they are promising in image and multidimensional signal processing applications. In addition, the synthesis scaling function in a BQCW system of any order is interpolating (or cardinal), which has been known as a desired merit in numerical analysis.

关键词： Filter bank Signal synthesis Image reconstruction Passband Frequency Image converters H infinity control Multidimensional signal processing Numerical analysis

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GMA Welding Process Regulation via Hierarchical GPC with Assured Stability

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IFAC Proceedings Volumes 1997年第3期30卷 221-226页

作者： S.G. Tzafestas E.J. Kyriannakis Intelligent Robotics and Automation Laboratory National Technical University of Athens Department of Electrical and Computer Engineering 15773 Zografou Campus Athens Greece

This paper deals with the regulation of the thermal characteristics of Gas Metal Arc (GMA) welding. A previously developed model is used for the open loop predictions. At the first level of the hierarchy, a parameterized Generalized Predictive Control (GPC) algorithm is selected among other control techniques, due to its robustness against modeling errors and parameter variations. A coordinator, at the second level of the hierarchy, specifies a set of reliable values for the parameters of GPC, so that stability is assured. A representative set of simulation results is included, along an evaluation of the advantages and limitations of the proposed hierarchical GPC technique.

关键词： Predictive control Hierarchical structures Regulation Stabilization Arc welding

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3D reconstruction of the human jaw from a sequence of images

3D reconstruction of the human jaw from a sequence of images

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Conference on computer vision and Pattern Recognition (CVPR)

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

A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.

关键词： Image reconstruction Humans computer vision Data acquisition Cameras Shape Data mining Genetic algorithms Implants Machine vision

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Two-stage neural network for volume segmentation of medical images

Two-stage neural network for volume segmentation of medical ...

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International Conference on Neural Networks

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

We present a system to segment and label CT/MRI brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be adapted to real-time imaging scenarios.

关键词： Neural networks Image segmentation Biomedical imaging Feature extraction Principal component analysis Computed tomography Magnetic resonance imaging Brain Labeling Clustering algorithms

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An invariant pulse-coder for 2-D shape recognition

An invariant pulse-coder for 2-D shape recognition

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International Conference on Information, Communications and Signal Processing

作者： N. Rishikesh Y.V. Venkatesh Computer Vision and Artificial Intelligence Laboratory Department of Electrical Engineering Indian Institute of Science Bangalore India

We present some novel schemes for (i) pulse coding for invariant representation of shape; and (ii) a neural architecture for recognizing the encoded shape. The proposed shape encoder utilizes the properties of complex logarithmic mapping (CLM) which transforms rotation and scaling (in its domain) to shifts (in its range). In order to handle this shift, in an attempt to provide increased speed of operation, the encoder converts the CLM output to a sequence of pulses. These pulses are fed to a novel multilayered neural recognizer which (i) invokes template matching with a distinct architecture; and (ii) achieves robustness (to noise and shape deformation) by virtue of its overlapping strategy for code classification. The proposed encoder-recognizer system, which is hardware implementable by a high-speed electronic switching circuit, and can add new shapes on-line to the existing ones, is illustrated by examples.

关键词： Pulse shaping methods Shape Pattern recognition Encoding Fires computer vision Artificial intelligence Laboratories computer architecture Noise robustness

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Modelling active contours using neural networks isomorphic to boundaries

Modelling active contours using neural networks isomorphic t...

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International Conference on Neural Networks

作者： Y.V. Venkatesh N. Rishikesh Computer Vision and Artificial Intelligence Laboratory Department of Electrical Engineering Indian Institute of Science Bangalore India

We propose a new technique, based on self-organization, for localizing salient contours in an image, with applications to, for instance, object and character recognition, stereopsis and motion tracking. A neuronal network which is isomorphic to the template/initial contour is created. This network acts as an active contour, which, using self-organization, undergoes deformation in an attempt to cling on to the nearest salient contour in the test image. The application areas of the model proposed are similar to "snake", but distinct from it both in the underlying mathematics and implementation. The new technique is illustrated with some examples.

关键词： Active contours Neural networks Humans Image edge detection Artificial intelligence Shape Character recognition Object recognition Prototypes Spline

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Probabilistic octree modeling of a 3D dynamic environment

Probabilistic octree modeling of a 3D dynamic environment

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IEEE International Conference on robotics and Automation (ICRA)

作者： P. Payeur P. Hebert D. Laurendeau C.M. Gosselin Computer Vision and Digital Systems Laboratory Department of Electrical and Computer Engineering Laval University Sainte Foy QUE Canada Computer Vision and Digital Systems Laboratory Department of Mechanical Engineering Laval University Sainte Foy QUE Canada

Probabilistic occupancy grids have proved to be very useful for workspace modeling in 2D environments. Due to the expansion of computational load, this approach was not tractable for mapping a 3D environment in real applications. In this paper, the original occupancy grid scheme is revisited and a generic closed-form function is introduced to avoid numerical computation of probabilities for a range sensor with Gaussian error distribution. Occupancy probabilities are computed and stored in a multiresolution octree for improved performance and compactness. Occupancy models are built in local reference frames and linked to a global reference frame through uncertain spatial relationships that can be updated dynamically. This scheme is used for building a 3D map in a telerobotic maintenance application of electric power lines where perturbations may cause motion of object assembly.

关键词： Layout computer vision Grid computing Spatial resolution Robotic assembly Solid modeling Bayesian methods Digital systems Mechanical engineering Distributed computing

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Robust telemanipulator control using a partitioned neural network architecture

Robust telemanipulator control using a partitioned neural ne...

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1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Tzafestas, SG Prokopiou, PA Tzafestas, CS Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical Unhersity of Athens Zografou 15773 Athens Greece Laboratoire de Robotique de Paris CNRS UPMC-UVSQ 78140 Velizy 10-12 AV. de 1' Europe France

ISBN: (纸本)0780341236

In this paper the control problem of telemanipulators is considered under the condition that they are subject to modeling and other uncertainties of considerable levels. The design is based on the S. Lee and H. S. Lee teleoperator control scheme, which is modified so as to be able to compensate the uncertainties, and is implemented using a partitioned multilayer perceptron neural network. Several subnetworks are used each one identifying a term of the manipulator's dynamic model. A new learning algorithm is proposed which distributes the learning error to each subnetwork and enables online training Several simulation results are provided which show the robustness ability by the partitioned neurocontroller, and compare it with the results obtained through sliding mode control.

关键词： Sliding mode control

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Introducing the theory of fuzzy cognitive maps in distributed systems

Introducing the theory of fuzzy cognitive maps in distribute...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： C.D. Stylios V.C. Georgopoulos P.P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rio Greece School of Electrical Engineering and Computer Science Ohio University Athens OH USA

This paper investigates a novel hybrid fuzzy neural system, fuzzy cognitive map (FCM), and its implementation in distributed systems and control problems. The description and the methodology of this system will be examined and then it will be shown the application of FCM in a process control problem, which will reveal the characteristics and qualities of FCM. There is an oncoming need for more autonomous and intelligent systems, which could be satisfied with the application of FCM in the field of systems and control.

关键词： Fuzzy cognitive maps Fuzzy systems Fuzzy logic Intelligent systems robotics and automation Fuzzy control Control systems Control system synthesis Neural networks Humans

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Using local 3D structure for segmentation of bone from computer tomography images

Using local 3D structure for segmentation of bone from compu...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： C.-F. Westin A. Bhalerao H. Knutsson R. Kikinis Surgical Planning Laboratory Harvard Medical School USA Computer Vision Laboratory Department of Electrical Engineering Linköping University Sweden

In this paper we focus on using local 3D structure for segmentation. A tensor descriptor is estimated for each neighbourhood, i.e. for each voxel in the data set. The tensors are created from a combination of the outputs form a set of 3D quadrature filters. The shape of the tensors describe locally the structure of the neighbourhood in terms of how much it is like a plane, a line, and a sphere. We apply this to segmentation of bone from computer Tomography data (CT). Traditional methods are based purely on gray-level value discrimination and have difficulties in recovering thin bone structures due to so called partial voluming, a problem which is present in all such sampled data. We illuminate the partial voluming problem by showing that thresholding creates complicated artifacts even if the signal is densely enough sampled and can be perfectly reconstructed. The unwanted effects of thresholding can be reduced by a change of the signal basis. We show that by using additional local structure information can significantly reduce the degree of sampling artifacts. Evaluation of the method on a clinical case is presented, the segmentation of a human skull from a CT volume. The method shows that many of the thin bone structures which disappear in a pure thresholding can be recovered.

关键词： Image segmentation Bones Tensile stress Computed tomography Image reconstruction Surgery Signal sampling Laboratories Shape Image sampling

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