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Solution of stereo correspondence in real scene: an analogic CNN algorithm

Solution of stereo correspondence in real scene: an analogic...

引用

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

作者： A.G. Radvanyi Analogic & Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary

A multilayer analogic CNN (cellular neural network) algorithm is proposed to reconstruct surfaces from real scene stereo-pairs consisting of two images shot from one and the same camera position. The whole scene is illuminated by randomly structured light to provide texture on otherwise "empty" surfaces. One image is that of the illuminated background, the other one is the image of illuminated objects in front of the same background.< >

关键词： Layout Cellular neural networks Image reconstruction Surface reconstruction Stereo vision Surface texture Matched filters Laboratories automation Nonhomogeneous media

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Collision prediction via the CNN Universal Machine

Collision prediction via the CNN Universal Machine

引用

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

作者： V. Gal T. Roska Analogical & Neural Computing Systems Laboratory at the computer Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Hungary

We present an analogic CNN algorithm that estimates the time to an impending collision between an approaching object and the observer. Calculation is based on a context insensitive method, which is well known in neuro... 详细信息

关键词： Cellular neural networks Turing machines Animals Equations Geometrical optics Object detection Image edge detection Detectors Pixel Optical arrays

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Adaptive histogram equalization with cellular neural networks

Adaptive histogram equalization with cellular neural network...

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

作者： M. Csapodi T. Roska Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Adaptive histogram equalization (AHE), a method of contrast enhancement which is sensitive to local spatial information in image, has demonstrated its effectiveness in many applications. However, this technique is computationally intensive. In this paper we present two computational methods designed to fit well onto the locally interconnected array computer architecture of cellular neural networks (CNNs). CNNs are well known for their image processing capabilities, specially for grey-scale medical images and images of a natural scene. In many applications it would be very useful if the operation of a template or a complex analogic algorithm were highly illumination independent. Our results suggest that we can achieve this goal by using the AHE method in a pre-processing step.

关键词： Histograms Adaptive equalizers Cellular neural networks Application software Adaptive systems computer networks Design methodology computer architecture Image processing Biomedical imaging

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Real-life application case studies using CMOS 0.8 /spl mu/m CNN universal chip: analogic algorithm for motion detection and texture segmentation

Real-life application case studies using CMOS 0.8 /spl mu/m ...

引用

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

作者： P. Foldesy A. Zarandy P. Szolgay T. Sziranyi Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Using a 20/spl times/22 CNN Universal Machine chip two application case studies are presented. A new analogic CNN algorithm is shown to detect objects having larger size than a given value on black-and-white image sequences moving in a given range of direction and speed (17 /spl mu/s processing speed could be achieved). An extremely fast texture classification analogic algorithm is given next with approximately 2 /spl mu/s processing speed and with less than 5% misclassification error rate for 4 natural textures in a real-life testing environment.

关键词： computer aided software engineering Cellular neural networks Switches Logic Motion detection Turing machines Testing Prototypes Registers Thyristors

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High speed stand-alone visual decision maker device based on focal plane analogic processor array chip

High speed stand-alone visual decision maker device based on...

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IEEE International Workshop on Virtual and Intelligent Measurement systems

作者： L. Torok A. Zarandy T. Roska Analogical & Neural Computing Systems Laboratory at Computer and Automation Research Institute of the Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)0780365682

Newly emerging problems require high speed decision making based on visual perception of the environment. A project was set up to construct an intelligent agent like self-contained device that is capable to act in real-time and show collaborative behavior. Giving the hardware basis for decisions to be made a cellular nonlinear network CNN (Chua and Yang, 1988) chip implementation's optical input is used in combination with the cooperative devices' information that is received via binary ports and serial ports. The proposed design is a self-contained compact device that is prepared to operate stand-alone for up to 10 hours running on medium sized batteries while doing measurements, logging and collaborating with its environment via parallel port (for image transfer), RS-232 port (using modbus, profibus, PPP protocols) and binary I/O-s. Intelligent power module, optical isolation, watch dog capability is also considered.

关键词： Collaboration High speed optical techniques Nonlinear optics Decision making Visual perception Intelligent agent Hardware Cellular networks Cellular neural networks Nonlinear optical devices

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CASTLE: an emulated digital CNN architecture design issues, new results

CASTLE: an emulated digital CNN architecture design issues, ...

引用

IEEE International Conference on Electronics, Circuits and systems (ICECS)

作者： A. Zarandy P. Keresztes T. Roska P. Szolgay Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

A new emulated digital CNN universal machine chip architecture is introduced in this paper. The chip contains 24 CNN core processors using 70 mm/sup 2/ silicon area with a 0.35 /spl mu/m technology. Its speed is 1 ns/virtual cells/CNN iterations with 12 bit precision. This enables one to execute over five hundred 3/spl times/3 convolutions on each frame of a 240/spl times/320 sized 25 fps (standard NTSC) digital image flow. Another new feature of the design is the different precision capability. This allows the user to convert precision to speed.

关键词： Cellular neural networks computer architecture Optical feedback Equations Turing machines Silicon Convolution Image processing Very large scale integration Biomedical optical imaging

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Distance preserving 1D Turing-wave models via CNN, implementation of complex-valued CNN and solving a simple inverse pattern problem (detection)

Distance preserving 1D Turing-wave models via CNN, implement...

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

作者： G. Toth P. Foldesy T. Roska Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper a cellular neural network (CNN) implementation of a reaction-diffusion system is described, which produces distance preserving periodic Turing patterns. The CNN with complex-valued templates are introduced, presenting an application for pattern generation. Finally a method for black-and-white pattern detection is described.

关键词： Cellular neural networks Equations Skin Marine animals Laboratories automation Physics Chemistry Biological system modeling Inhibitors

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The computational infrastructure for cellular visual microprocessors

The computational infrastructure for cellular visual micropr...

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Proceedings of the International Conference on Microelectronics for neural, Fuzzy and Bio-Inspired systems, MicroNeuro

作者： P. Szolgay A. Zarandy S. Zold T. Roska P. Foldesy L. Kek T. Kozek K. Laszlo I. Petras Cs. Rekeczky I. Szatmari D. Balya Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

A new computational paradigm is emerging for spatio-temporal problems: analogic CNN array-computing. The elementary instructions and programming techniques, however, are drastically different from any other computers. These elementary instructions represent complex, spatio-temporal, nonlinear, dynamic phenomena including all the standard and exotic properties of simple image processing operators as well as waves, patterns, and "evolving systems". Meanwhile, a computational infrastructure has also emerged interfacing this revolutionary computing technology to digital systems as well as enabling the development of high-level software. The main goal was to provide easy-to-use tools and hardware interfacing elements, and to put most of the sophistication in the chips and chip sets.

关键词： Microprocessors Cellular neural networks Prototypes computer aided instruction Image processing Digital systems Hardware Turing machines Embedded computing CMOS technology

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Optimal CNN templates for deconvolution

Optimal CNN templates for deconvolution

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

作者： L. Orzo Analogical & Neural Computing Systems Laboratory at the Computer and Automation Research Institute of the Hungarian Academy of Sciences Budapest Hungary

A simplified version of the gradient descent method is introduced as a straightforward way to find optimal 3/spl times/3 CNN templates for the inversion of known point spread functions (PSF). In practical applications the determination of this inverse is necessary to fulfil deconvolution tasks. The proposed method is much faster than the previously applied algorithms (like genetic algorithm) and still, in almost all practically important cases, it is convergent. Moreover, unlike a closed form method, it leads to 3/spl times/3 templates instead of 5/spl times/5 or bigger ones. In several important practical cases the PSF, which can be caused by motion, out of focus or the aberration of the imaging system, can be computed from object positions and from the optical system's parameters. Iterative deconvolution algorithms, which are necessary for volume reconstruction from microscopic image sequences, require considerable computation time. Using CNN-UM chips for these deconvolution tasks, a much higher speed, even real time processing seems to be achievable.

关键词： Cellular neural networks Deconvolution Genetic algorithms Focusing Optical imaging Optical computing Iterative algorithms Image reconstruction Microscopy Image sequences

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An emulated digital architecture implementing the CNN Universal Machine

An emulated digital architecture implementing the CNN Univer...

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

作者： A. Zarandy P. Keresztes T. Roska P. Szolgay Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

An emulated digital VLSI CMOS architecture is described, where the main features are as follows: (i) variable accuracy, (ii) a complete CNN Universal Machine on the silicon, (iii) a good area time trade off. The whole architecture was defined on VHDL and the following key parameters of the implementation were computed namely, (i) the speed (1 ns/virtual cell/iteration), (ii) the number of the physical processing cells per cm/sup 2/ is 24 by using 0.35 /spl mu/m three metal layer CMOS technology.

关键词： Cellular neural networks Turing machines computer architecture CMOS technology Physics computing Digital signal processing Logic Very large scale integration CMOS process Silicon

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