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image inpainting methods by using CELLULAR neural networks

Image inpainting methods by using CELLULAR neural networks

引用

9th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA

作者： Gacsádi, Alexandra Szolgay, Péter Electronics Department University of Oradea Str. Armatei Române Nr.5 410087 Oradea Romania Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 H-1502 Budapest Hungary Image Processing and Neurocomputing Department Veszprém University Egyetem u. 10 Veszprém Hungary

Some CNN methods are presented that can be used for the reconstruction of damaged or partially known images. The proposed methods take the possibility of direct implementation on an existing CNN chip into account, in a single step, by using 3*3 dimensional linear reaction templates. Due to complete parallel processing, computational time reduction is achieved. Efficiency of these methods can be increased by combining them with nonlinear template that ensures the growth of the local properties spreading area along with regional ones.

关键词： Cellular neural networks

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image inpainting methods by using cellular neural networks

Image inpainting methods by using cellular neural networks

引用

IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： A. Gacsadi P. Szolgay Electronics Department University of Oradea Oradea Romania Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Image Processing and Neurocomputing Department Veszprem University Veszprem Hungary

关键词： Cellular neural networks image processing image restoration Partial differential equations image reconstruction Parallel processing Concurrent computing Cost function Gray-scale Laboratories

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Automated Characterization of cellular migration phenomena

Automated Characterization of cellular migration phenomena

引用

2005 IEEE Computational Systems Bioinformatics Conference, Workshops and Poster Abstracts

作者： Beaudry, Christian Berens, Michael E. Doker, Tarek El Joy, Anna M. Karam, Lina J. Lacroix, Zoe Lutfi, Jad A. Motoru, Sai Renaut, Rosemary A. Rich, Ian J. Translational Genomics Research Institute Phoenix AZ United States Department of Electrical Engineering Machine Perception Laboratory Northern Arizona University United States Department of Electrical Engineering Image Video and Usability and Multi-D Signal Processing Labs. Arizona State University United States Department of Mechanical and Aerospace Engineering Scientific Data Management Lab. Arizona State University United States Department of Mathematics Computational Biosciences Program Arizona State University United States

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On using type-1 fuzzy set mathematics to derive interval type-2 fuzzy logic systems

On using type-1 fuzzy set mathematics to derive interval typ...

引用

Conference of the North American Fuzzy Information processing Society - NAFIPS

作者： J.M. Mendel R.I. John Feilong Liu Signal and Image Processing Institute Department of Electrical Engineering University of Southern California Los Angeles CA USA Centre for Computational Intelligence Department of Computer Science Faculty of Computing Science and Engineering De Montfort University Leicester UK

In this paper, we demonstrate that it is unnecessary to take the route from general type-2 fuzzy set to interval type-2 fuzzy set, and that all of the results that are needed to implement an interval type-2 fuzzy logic system can be obtained using type-1 fuzzy set mathematics. As such, this paper makes an interval type-2 fuzzy logic system much more accessible to the fuzzy logic community, and we can now develop an interval type-2 fuzzy logic system in a much more straightforward way.

关键词： Fuzzy logic Fuzzy sets Fuzzy systems mathematics Frequency selective surfaces Signal processing image processing Computational intelligence computer science Uncertainty

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Concept Oriented Imitation Towards Verbal Human-Robot Interaction

Concept Oriented Imitation Towards Verbal Human-Robot Intera...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： H. Mobahi M.N. Ahmadabadi B.N. Araabi Control and Intelligent Processing Centre of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran

Imitation equips robots with a simple and natural interface to learn new tasks. Although abstraction is a remarkable feature of imitation that discriminates it from mimicking, there has been no enough research on this dimension of imitation. Relational concepts are the simplest type of abstract concepts and can be an appropriate start point. These concepts may be learned by combining perceptual categorization and classical conditioning. The paper will first formalize relational concept learning within an imitative context. Internal modules of the learning agent are considered to be functions. We will prove that in this case the concept-motor mapping becomes one-to-one which simplifies learning. A learning algorithm for the model will be also proposed and evaluated in a phoneme acquisition experiment with a large number of highly overlapped samples.

关键词： Cognitive robotics Intelligent robots Learning Humans Robotic assembly Process control Intelligent control Senior citizens Positron emission tomography Educational robots

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Optimal sub-shape models by minimum description length

Optimal sub-shape models by minimum description length

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： G. Langs P. Peloschek H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Department of Clinical Radiology Vienna Medical University Vienna Austria

Active shape models are powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowledge in an efficient and gainful way. However, due to the linearity of PCA, non-linearities like rotations or independently moving sub-parts in the data can deteriorate the resulting model considerably. Although non-linear extensions of active shape models have been proposed and application specific solutions have been used, they still need a certain amount of user interaction during model building. In this paper the task of building/choosing optimal models is tackled in a more generic information theoretic fashion. In particular, we propose an algorithm based on the minimum description length principle to find an optimal subdivision of the data into sub-parts, each adequate for linear modeling. This results in an overall more compact model configuration. Which in turn leads to a better model in terms of modes of variations. The proposed method is evaluated on synthetic data, medical images and hand contours.

关键词： Active shape model Biomedical imaging Principal component analysis computer vision Linearity Polynomials Pattern recognition computer graphics Radiology image processing

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Background suppression based-on wavelet transformation to detect infrared target

Background suppression based-on wavelet transformation to de...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Jin-Wen Tian Jian Liu State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China School of Information and Mathematics Yangtze University Jinzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image would be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical.

关键词： Infrared detectors Object detection Infrared imaging Target tracking Marine vehicles Clouds image segmentation Wavelet analysis Wavelet domain Signal analysis

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Radar backscattering model for multilayer mixed-species forests

Radar backscattering model for multilayer mixed-species fore...

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作者： Liang, Pan Moghaddam, Mahta Pierce, Leland E. Lucas, Richard M. IEEE Atmospheric and Environmental Research Inc. Lexington MA Department of Electrical Engineering and Computer Science Radiation Laboratpry University of Michigan Ann Arbor URSI Commission B Electromagnetics Academy Phi Kappa Phi Tau Beta Pi Eta Kappa Nu Microwave Image Processing Facility Within the Radiation Laboratory Electrical Engineering and Computer Science Department University of Michigan University of Wales Aberystwyth Aberystwyth United Kingdom Radiation Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109-2122 United States Institute of Geography and Earth Sciences University of Wales Aberystwyth SY23 3DB United Kingdom

A multilayer canopy scattering model is developed for mixed-species forests. The multilayer model provides a significantly enhanced representation of actual complex forest structures compared to the conventional canopy-trunk layer models. Multilayer Michigan Microwave Canopy Scattering model (Multi-MIMICS) allows overlapping layer configuration and a tapered trunk model applicable to forests of mixed species and/or mixed growth stages. The model is the first-order solution to a set of radiative transfer equations and includes layer interactions between overlapping layers. It simulates SAR backscattering coefficients based on input dimensional, geometrical, and dielectric variables of forest canopies. The Multi-MIMICS is an efficient realization of actual forest structures and can be shaped for specific interest of forest parameters. We present the model's application and validation in the paper. The model is parameterized using data collected from a 220 000-ha area of forests in central Queensland, Australia. Fifteen 50 × 50 m test sites representing the general forest diversity and growth stages are chosen as ground truth. Polarimetric backscattering Airborne SAR (AIRSAR) data of the same area are acquired to validate the model simulations. The model predicts SAR backscattering coefficients of the test areas. Simulation results show a good agreement with AIRSAR data at most frequencies and polarizations. The simulated backscattering coefficient from the multilayer model and the standard MIMICS are also compared and significant improvements are observed. © 2005 IEEE.

关键词： Mathematical models

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DSA image registration based on multiscale Gabor filters and mutual information

DSA image registration based on multiscale Gabor filters and...

引用

International Conference on Information and Automation (ICIA)

作者： Zhiguo Cao Xiaoxiao Liu Bo Peng Yiu-Sang Moon Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Chinese University of Hong Kong New Territories Hong Kong China

In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in X-ray image sequences. Different with traditional DSA image registration processes, in our proposed image registration method, the control points are selected from the vessel centerlines using multiscale Gabor filters, and mutual information (MI) is then taken as the similarity criterion to find the correspondences. Experimental results demonstrate our algorithm efficiently yields satisfying registration result for DSA images.

关键词： image registration Gabor filters Mutual information Biomedical imaging Angiography Visualization Displacement control Blood vessels image sequences Pixel

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Learning distributed grasp in presence of redundant agents

Learning distributed grasp in presence of redundant agents

引用

IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： A.H. Elahibakhsh M. Nili Ahmadabadi F. Janabi-Sharifi B. Nadjar Araabi AI & Robotics Laboratory Center of Excellence for Control and Intelligent Processing Department of Electrical and Computer Eng. Institute for Studies on Theoretical Physics and Mathematics University of Tehran Tehran Iran Robotics and Manufacturing Automation Lab Department of Mechanical and Industrial Engineering Ryerson University Toronto ONT Canada

Learning distributed object grasp by a group of robots with redundant members is the main focus of this paper. In Elahibakhsh, A. H., et al. (2004), we tackled the problem of learning form closure grasp for planar convex objects by multiple non-communicating robots without any information about the shape of objects. In this paper, the problem in presence of redundant agents is investigated. Agents' states and actions are designed such that the group learns grasping different objects using Q-learning method. As the environment is not intelligent enough to assess each agent's effect on the team performance, a credit assignment algorithm based on knowledge evaluation is designed. The proposed method considers the environment credit for the team, number of redundant agents, and the expertness level of each agent in its credit assignment. Applicability of the designed approach is verified through a set of simulations. It is shown that the team learns grasping different objects. Therefore, it is expected that the proposed method can be extended for distributed grasp of deformable objects

关键词： Intelligent robots Learning Robot sensing systems Shape Cognitive robotics Robotics and automation Intelligent agent Algorithm design and analysis Grasping Redundancy

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