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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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Application of panoramic annular lens for motion analysis tasks: surveillance and smoke detection

Application of panoramic annular lens for motion analysis ta...

引用

International Conference on Pattern Recognition

作者： I. Kopilovic B. Vagvolgyi T. Sziranyi Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary Analogical and Neural Computing Laboratory Comp. and Aut. Institute Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)0769507506

In this paper some applications of motion analysis are investigated for a compact panoramic optical system (panoramic annular lens). Panoramic image acquisition makes multiple or mechanically controlled camera systems needless for many applications. Panoramic annular lens' main advantage to other omnidirectional monitoring systems is that it is a cheap, small, compact device with no external hyperboloidal, spherical, conical or paraboloidal reflecting surface as in other panoramic optical devices. By converting the annular image captured with an NTSC camera to a rectangular one, we get a low-resolution (2.8 pixels/degrees horizontally and 3 pixels/degree vertically) image. We developed algorithms which can analyze this low-resolution image to yield motion information for surveillance and smoke detection.

关键词： Lenses Motion analysis Cameras Pixel Control systems Monitoring Optical devices image converters image analysis image motion analysis

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Dynamic training of hand gesture recognition system

Dynamic training of hand gesture recognition system

引用

International Conference on Pattern Recognition

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

We developed an augmented reality tool for vision-based hand gesture recognition in a camera-projector system. Our recognition method uses modified Fourier descriptors for the classification of static hand gestures. Hand segmentation is based on a background subtraction method, which is improved to handle background changes. Most of the recognition methods are trained and tested by the same service-person, and training phase occurs only preceding the interaction. However, there are numerous situations when several untrained users would like to use gestures for the interaction. In our new practical approach the correction of faulty detected gestures is done during the recognition itself. Our main result is the quick on-line adaptation to the gestures of a new user to achieve user-independent gesture recognition.

关键词： Computer displays Cameras Fault detection Mice Hardware Phase detection System testing Feedback Auditory displays image processing

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An advanced real-time, multi-channel emulated-digital retina model implementation on FPGA

An advanced real-time, multi-channel emulated-digital retina...

引用

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

作者： Zsolt Voroshazi Zoltan Nagy Peter Szolgay Department of Image Processing and Neurocomputing University of Pannonia Veszprem Hungary Cellular Sensory and Wave Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Various channels of the neuromorphic, multi-layer retina has been successfully modeled by CNN. Our primary aim was to build up a real-time test environment with camera input and display output in order to mimic the behavior of retina model implementation on emulated digital CNN by using a low-cost, moderate sized field-programmable gate array (FPGA) architecture.

关键词： Retina Field programmable gate arrays Computational modeling Adaptation model Real time systems Biological system modeling Mathematical model

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Supervised training based hand gesture recognition system

Supervised training based hand gesture recognition system

引用

International Conference on Pattern Recognition

We have developed a hand gesture recognition system, based on the shape analysis of static gestures, for human computer interaction purposes. Our appearance-based recognition uses modified Fourier descriptors for the classification of hand shapes. As always found in literature, such recognition systems consist of two phases: training and recognition. In our new practical approach, following the chosen appearance-based model, training and recognition is done in an interactive supervised way: the adaptation for untrained gestures is also solved by hand signals. Our experimental results with three different users are reported. Besides describing the recognition itself we demonstrate our interactive training method in a practical application.

关键词： Shape Character recognition image processing Laboratories Automation Human computer interaction Application software Control systems Virtual environment Cameras

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

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

引用

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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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 compression by orthogonal decomposition and dynamic segmentation using cellular nonlinear network chips

Image compression by orthogonal decomposition and dynamic se...

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

作者： T. Sziranyi L. Czuni I. Kopilovic T. Gyimesi Analogical and Neural Computing Laboratory Hungarian Academy of Sciences Computer and Automation Institute Budapest Hungary Department of Image Processing 8z Neurocomputing University of Veszprém Veszprem Hungary

A method is shown using the CNN chip-set hardware architecture for the implementation of a high-speed, low bit-rate image coding system. A simple and fast algorithm is introduced to generate basis functions of 2 dimensional (2D) orthogonal transformations. Using the 2D basis functions of the Hadamard or Cosine functions, the transformation coefficients of the basic block of the image are measured by the CNN. Meanwhile, the CNN can produce the inverse transformation of the measured coefficients and the actual distortion-rate can be computed. If a required distortion-rate is reached, the coding process could be stopped (the use of even more coefficients would increase bit-rate needlessly). Effects of noise and VLSI computing accuracy are also considered to optimise the architecture. We also give a short description of how to join the transform coding method and the object-oriented image model.

关键词： image coding image segmentation Discrete cosine transforms Cellular neural networks Object oriented modeling Optimization methods Computer networks Distortion measurement Nonlinear distortion Very large scale integration

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Optical detection of breaks and short circuits on the layouts of printed circuit boards using CNN

Optical detection of breaks and short circuits on the layout...

引用

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

作者： P. Szolgay K. Tomordi Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Image Processing and Neurocomputing Department Faculty of Engineering University of Veszprem Veszprem Hungary

The printed circuit board layout inspection methods are mostly based on local geometric information, therefore it is well suited to the cellular neural network (CNN) paradigm. Two layout errors are detected here namely, the breaks in the wires and some kind of short circuits. The designed analogic algorithms to solve the problems above were tested on real life examples using an experimental system based on our CNN-HAC1M digital multiprocessor add-on-board, with 1 million cell space and 2.0 /spl mu/s/cell/iteration speed.

关键词： Optical detectors Cellular neural networks Geometrical optics Optical computing Printed circuits Inspection Wires Algorithm design and analysis Circuit testing Life testing

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image inpainting methods by using cellular neural networks

Image inpainting methods by using cellular neural networks

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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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