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Motion segmentation and tracking optimization with edge relaxation in the cellular nonlinear network architecture

Motion segmentation and tracking optimization with edge rela...

引用

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

作者： L. Czuni T. Sziranyi Department of Image Processing and Neurocomputing University of Veszpém Veszprem Hungary Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary

We have developed a high-level set of cellular neural net (CNN) functions for finding the segment-borders of moving objects through spatio-temporal relaxation optimization. They are analogic algorithms based on simple CNN instructions considering their implementability in analogic VLSI chips. Motion information extraction from video series is very power consuming. Most computing effort is devoted to motion vector field estimation, object definition and boundary determination. Finding interrelations among small segments, obtained by oversegmentation, involves optimization through merging or separation. In our algorithm the process starts from an oversegmented image, then the segments are merged using information from spatial and temporal auxiliary data: motion fields and motion history. This grouping process is based on neighboring segment similarity in color, speed and time-depth. There is also a feedback to accept or refuse the cancellation of a segment-border. Our parallel approach is independent of the number of segments or objects. We use simple VLSI functions. We develop grouping by stochastic optimization. This relaxation-based motion segmentation can be a basic step of the effective coding of image-series and other automatic motion tracking systems. The proposed system is planned to implement in a cellular nonlinear network chip-set architecture.

关键词： Motion segmentation computer vision Tracking image segmentation Cellular neural networks Very large scale integration Neural networks Data mining Motion estimation Merging

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Error analysis for quadtree image formation

Error analysis for quadtree image formation

引用

IEEE International Conference on image processing

作者： L.M. Kaplan Seung-Mok Oh M. Cobb J.H. McClellan Department of Engineering Clark Atlanta University Atlanta GA USA Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0780362977

The quadtree image formation technique is a computationally efficient approximation to standard backprojection. Where the computational load of backprojection is O(N/sup 3/) for N sensors forming an N/spl times/N image, the quadtree method uses a divide-and-conquer strategy similar to the fast Fourier transform (FFT) to reduce the computational load down to O(N/sup 2/ log(N)). However, the quadtree introduces errors in the relative time shifts used to focus pulses. These errors reduce the signal gain in the mainlobe response for isotropic point-like targets. In addition, the oscillations of the sidelobes increase from stage to stage. This paper develops performance bounds for the mainlobe losses under far field conditions and relates these bounds to the slow-time Nyquist rate.

关键词： Error analysis Synthetic aperture radar Radar scattering Layout Radar imaging Frequency image sensors Ultra wideband radar Motion compensation Geometry

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Spatio-temporal segmentation with edge relaxation and optimization using fully parallel methods

Spatio-temporal segmentation with edge relaxation and optimi...

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International Conference on Pattern Recognition

作者： T. Sziranyi L. Czuni Analogical and Neural Computing Laboratory Computer & Aut. Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary

ISBN: (纸本)0769507506

In this paper we outline a fully parallel and locally connected computation model for the spatio-temporal segmentation of motion events in video sequences. We are searching for a new algorithm, which can be easily implemented in one-pixel/one-processor cell-array VLSI architectures at high-speed. Our proposed algorithm starts from an oversegmented image, then the segments are merged by applying the information coming from the spatial and temporal auxiliary data: motion fields and motion history, which is calculated from consecutive image frames. This grouping process is defined through a similarity measure of neighboring segments, which is based on the values of intensity, speed and the time-depth of motion history. As for checking the merging process there is a feedback implemented, by that we can accept or refuse the cancellation of a segment-border. Our parallel approach is independent of the number of segments and objects, since instead of graph representation and serial processing of these components, image features are defined on the pixel-level. We use simple functions, easily realizable in VLSI, like arithmetic and logical operators, local memory transfers and convolution.

关键词： image segmentation Very large scale integration History Concurrent computing Computational modeling Video sequences computer architecture Motion measurement Velocity measurement Merging

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A comparison of the different CNN implementations in solving the problem of spatiotemporal dynamics in mechanical systems

A comparison of the different CNN implementations in solving...

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

作者： P. Szolgay T. Hidvegi Z. Szolgay P. Kozma Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Mechanics Technical University of Budapest Budapest Hungary Image processing and Neurocomputing University of Veszprém Veszprem Hungary

The large computing power of cellular neural networks (CNNs) is used to compute the transient response of a mechanical vibrating system. A basic question is how an inhomogeneous mechanical system can be computed by using different CNNUM (cellular neural net Universal Machine ) implementations. How complexity to time transformations were used in different CNNUM implementations, namely in software, in emulated digital CNN chips and in analog chips is discussed.

关键词： Cellular neural networks Spatiotemporal phenomena Mechanical systems computer networks Equations Damping Boundary conditions Laboratories Automation Transient response

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A joint source-channel coding approach to network transport on digital video

A joint source-channel coding approach to network transport ...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： B. Kurceren J.W. Modestino Dept. of Electr. Comput. & Syst. Eng. Rensselaer Polytech. Inst. Troy NY USA Electrical Computer and Systems Engineering Department Center for Image Processing Research Rensselaer Polytechnic Institute Troy NY USA

The use of forward error-control (FEC) coding, possibly in conjunction with passive-error recovery techniques, has emerged as a promising approach for real-time video transport over ATM networks for cell loss recovery and/or bit error correction, such as might be required for wireless links. Although FEC provides cell-loss recovery, through its erasure correcting capabilities, it also introduces transmission overhead which can possibly cause additional cell losses. A joint source-channel coding methodology is described to maximize the number of video sources multiplexed at a given quality of service (QoS), measured in terms of overall reproduced video quality. The transport channel is modeled as a block interference channel (BIC) and the multiplexer as a single server, deterministic service, finite buffer supporting N users. Based upon an information-theoretic characterization of the BIC and large deviation bounds on the buffer overflow probability, we describe a methodology that provides theoretically achievable upper limits on the number of sources multiplexed at a given level of performance. Performance of a specific coding technique using an MPEG-2 source encoder and interlaced non-binary Reed-Solomon (RS) channel codes is illustrated and shown to approach the information-theoretic predictions with increasing levels of complexity.

关键词： Forward error correction Quality of service Error correction Asynchronous transfer mode Error correction codes Propagation losses Interference channels Multiplexing Buffer overflow Reed-Solomon codes

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A computer algorithm for cancer recognition on ultrasound images of prostate tissue

A computer algorithm for cancer recognition on ultrasound im...

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1999 International Conference on Information Intelligence and Systems, ICIIS 1999

作者： Yfantis, E.A. Lazarakis, T. Bebis, G. Gallitano, G.M. Image Processing Laboratory Computer Science Department University of Nevada Las Vegas89154-4019 United States Computer Science Department University of Nevada RenoNV89557 United States Department of Mathematics West Chester University West Chester PennsylvaniaPA19383 United States

ISBN: (纸本)0769504469

An improvement of our previous computer algorithm of cancer recognition of ultrasound images is developed. In order for cancer to survive it develops its own blood supply system, which is different than the supply system of normal tissue. The velocity of the blood flowing through the cancerous blood vessels is different than the velocity of the blood flowing through blood vessels of normal tissue. Due to this fact, the ultrasound signal is absorbed differently in the cancerous areas than in the normal tissue areas. The energy of the signal, the continuity of the signal, autocorrelation function, and frequency domain properties are different in the normal tissue than in cancerous tissue. All these indicators are used for classifying the image of the tissue as being cancerous or non cancerous. © 1999 IEEE.

关键词： Blood vessels

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Video image retrieval on the basis of subregional co-occurrence matrix texture features and normalised correlation

Video image retrieval on the basis of subregional co-occurre...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Kyuheon Kim Seyoon Jeong Byung Tae Chun Jae Yeon Lee Younglae Bae Image Processing Department Computer Software Technology Laboratory Electronics and Telecommunications Research Institute Daejeon South Korea

This paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore, this paper proposes a simple segmentation method, which is to divide an image into high and low entropy regions by using picture information measure (PIM). Also, in order to describe texture characteristics of each region, this paper suggests six different texture features produced on the basis of co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of each texture feature values. Finally, this proposed algorithm is applied to various images and produces competitive results.

关键词： image retrieval image segmentation Multimedia databases Information retrieval Content based retrieval Entropy image databases image processing Telecommunication computing Software

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Entropy and color correlation for image indexing

Entropy and color correlation for image indexing

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IEEE International Conference on Systems, Man and Cybernetics

作者： Se Yoon Jeong Kyuheon Kim Byung Tae Chun Jae Yeon Lee Y.L.J. Bae Department of Image Processing Electronics and Telecommunications Research Institute Computer and Software Technology Laboratory Taejon South Korea

This paper presents a new indexing system, which divides an image into higher and lower entropy regions, and calculates the color correlation features between each type of region. Thus, we can improve the discrimination power of color indexing techniques. The indexing system proposed in this paper has three important properties. The first is an entropy feature. An image is divided by an entropy feature into two regions, lower and higher entropy regions in order to avoid the problems caused by general global features. The second is a color correlation feature. This paper uses 2-dimensional probability distribution functions of an image to obtain color moment features, and thus, obtain more information than using 1-dimensional probability distribution functions (i.e. histogram). The last is the retrieval procedure consisting of two steps: firstly, a simple retrieval algorithm is applied to all the images in a database, and secondly, only the results of the previous retrieval are searched. Thus, it can help in reducing the total retrieval time and improving the retrieval accuracy.

关键词： Entropy Indexing Histograms image retrieval Information retrieval Probability distribution Moment methods image databases Spatial databases image processing

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Efficient video images retrieval by using local co-occurrence matrix texture features and normalised correlation

Efficient video images retrieval by using local co-occurrenc...

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IEEE Region 10 International Conference TENCON

Since multimedia data is widely used in many fields, research is needed on how to search that data. As a method of retrieving multimedia data, especially for image data, content based image retrieval (CBIR) systems have obtained lots of interest. In order to develop CBIR systems, many different properties of an image have been considered for methods of retrieving image data such as colour, texture, shape, etc. The paper proposes a simple and efficient image retrieval algorithm, which retrieves images on the basis of subregional texture characteristics. In order to retrieve images in terms of contents, it is in general required to obtain a precise segmentation. However, it is very difficult and takes a lot of computing time for precise segmentation. Therefore, the proposed algorithm subdivides an image in terms of a certain sized windows, and finds out whether an image contains a query pattern on the basis texture features. Also, these texture features are described by only six different texture features produced from a co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of texture feature values. Finally, the proposed algorithm is applied to various images and produces competitive results.

关键词： image retrieval Information retrieval Content based retrieval image segmentation Multimedia databases Multimedia systems Shape image processing Telecommunication computing Software

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An effective method for combining multiple features of image retrieval

An effective method for combining multiple features of image...

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IEEE Region 10 International Conference TENCON

作者： Seyoon Jeong Kyuheon Kim Byungtae Chun Jaeyeon Lee Y.J. Bae Department of Image Processing Computer & Software Technology Laboratory Electronics and Telecommunications Research Institute Taejon South Korea

We propose an image retrieval system using the Borda count method in combining multiple experts (CME). It combines color-, shape- and texture-based retrieval systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

关键词： image retrieval Pattern recognition Shape Equations Fuzzy neural networks image processing Telecommunication computing Software Laboratories Content based retrieval

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