In this paper it is shown how the Cellular neural Network (CNN) can be used to perform image and volume deblurring, with particular emphases on applications to microscopy. We discuss the basic linear theory of the CNN...
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In this paper it is shown how the Cellular neural Network (CNN) can be used to perform image and volume deblurring, with particular emphases on applications to microscopy. We discuss the basic linear theory of the CNN including issues of stability and template size. It is observed that a CNN with a small template can be used to implement an Infinite Impulse Response filter. It is then shown how general deblurring problems can be addressed with a CNN when the blurring operator is known. The proposed application is to solve the basic 3-D confocal image reconstruction task about the form of the blurring operator, confocal behavior in microscope images can be obtained with only 3-5 acquired image planes. In addition, the stored program capability of the CNN Universal Machine would provide integration of several image processing and detection tasks in the same architecture.< >
An effective new character recognition procedure implemented on a new type of hardware system is proposed. This procedure applied a new architecture, called CNND. This CNND contains one or more analog cellular neural ...
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An effective new character recognition procedure implemented on a new type of hardware system is proposed. This procedure applied a new architecture, called CNND. This CNND contains one or more analog cellular neural Networks (CNN) and some digital logic, incorporating the advantages of the fast analog CNN signal processing and the fast and easy decision capability of digital logics. This paper shows that this CNND system can be used for recognition of multifont printed or handwritten characters. Implemented in hardware, the system could hit the 100 000 char/s recognition speed with a recognition rate of more than 95 %. We show that the CNN results of pictures (maximum 40 * 40 pixels) of printed characters can be coded into about n * 20 bits (n = 2 ... 6) , so the coded results can be used to address memories of about 1 MB. The codes of CNN results of possible character pictures are used to address the memories while the memory contents are filled by the character categories. Prior to the hardware implementation the decision memories are filled by the results of recognition simulation for the possible pictures of each character-class in a filling procedure. In the memory filling procedure the simulated recognition uses a new random-type nearest neighbor (NN) method, which is ideal for the recent proposal of hardware applications. Recognition of handwritten characters is demonstrated in the same system with good recognition accuracy.
The Cellular neural Networks (CNN) providing for efficient analog array processing of images are used for revealing surface features hidden in different types of random-dot stereograms (RDS) coding 3D information in i...
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The goals, objectives, characteristics, prerequisites, and courses of an information technology curriculum developed at the University of Veszprem in Hungary are discussed. Basic, introductory, and core courses as wel...
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The goals, objectives, characteristics, prerequisites, and courses of an information technology curriculum developed at the University of Veszprem in Hungary are discussed. Basic, introductory, and core courses as well as special subjects are listed, and the program schedule of the five years is presented. The place and role of information engineering in a changing world is discussed, including some thoughts on the role of information technology in the general university curricula.< >
A two-layer continuous-time cellular neural network for finding the Radon transform of a binary image is presented. The functionality of this cellular neural network follows from the functionality of the connected com...
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A two-layer continuous-time cellular neural network for finding the Radon transform of a binary image is presented. The functionality of this cellular neural network follows from the functionality of the connected component detector cellular neural network.
The programmability (as a stored program) of the CNN Universal Machine is discussed first. It is shown why and in which sense this machine is universal. A new type of algorithm, the analogic one, is introduced. The ap...
Various types of CNNs are summarized and the taxonomy of CNN is given according to the different types of grids, processors, interactions, and modes of operation. Next, the CNN Universal Machine is introduced. The arc...
A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In t...
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A new statistical pattern recognition method has been developed for detection, recognition or measurement of patterns which are (much) smaller than the measure of the elementary pixel windows in the image screen. In this measurement the gray-level histogram of the objects examined is compared with the simulated histograms of different (in type or size) possible objects, and the recognition (of shape or measure) is taken on the basis of the comparison. This method does not need ultra-precise movement of the scanning sensors or any additional hardwares. Moreover, the examined pattern should be randomly distributed on the screen, or a random movement of camera (or target or both) is needed. Effect of noises are analyzed, and filtering processes are suggested in the histogram domain. Several examples of different shapes are presented through simulations and experiments.< >
Cellular neural networks (CNNs) are considered here as cellular analog programmable multidimensional processing arrays with distributed logic and memory. The interconnecting weights between the neighbouring processing...
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For pt.I, see ibid., p.1-10 (1992). The programmability (as a stored program) of the CNN universal machine is discussed. It is shown why and in which sense this machine is universal. The analogic type of algorithm is ...
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For pt.I, see ibid., p.1-10 (1992). The programmability (as a stored program) of the CNN universal machine is discussed. It is shown why and in which sense this machine is universal. The analogic type of algorithm is introduced. The application potential is reviewed and the biological relevance is analyzed. It is shown that the architecture is optimal not only for silicon implementations, but also for many biological information processing organs that have the same structure.< >
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