Csaba Rekeczky

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In this paper, a CNN based spatio-temporal approach is introduced for finding the endocardial (inner) boundary of the left ventricle from a sequence of echocardiographic images. The discussed analogic1 CNN algorithm combines optimal nonlinear filtering and constrained wave propagation in order to estimate the continuous contour of a moving object in a(More)
In this paper, we develop a common cellular neural network framework for various adaptive nonlinear filters based on robust statistic and geometry-driven diffusion paradigms. The base models of both approaches are defined as difference-controlled nonlinear CNN templates while the self-adjusting property is ensured by simple analogic (analog and logic) CNN(More)
A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision(More)
In this paper, a vertebrate retina model is described based on a cellular neural network (CNN) architecture. Though largely built on the experience of previous studies ([5], [11], [14]-[15], [17]-[18]) the CNN computational framework is considerably simplified: first order RC cells are used with space-invariant nearest neighbor interactions only. All(More)
In this study, we present the initial results of cellular neural network (CNN)-based autowave metric to high-speed pattern recognition of gray-scale images. the application is to a problem involving separation of metallic wear debris particles from air bubbles. This problem arises in an optical-based system for determination of mechanical wear. This paper(More)
This report describes analogic algorithms used in the preprocessing and segmentation phase of off-line handwriting recognition tasks. A segmentation based handwriting recognition approach is discussed i.e. the system attempts to segment the words into their constituent letters. In order to improve their speed, the utilized CNN algorithms, whenever possible,(More)
In this paper a biologically motivated image flow processing mechanism is presented for visual exploration systems. The intention of this multi-channel topographic approach was to produce decision maps for salient feature localization and identification. As a unique biological study has recently confirmed, mammalian visual systems process the world through(More)