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This Letter presents an effective edge detection technique based on the cellular neural network paradigm. The approach exploits a rigorous model of the image contours and takes into account some electrical restrictions of existing hardware implementations. The method yields accurate results, better than the ones achievable by other cellular neural network-based techniques. [ABSTRACT FROM AUTHOR]

Presents analogic cellular neural network (CNN) algorithms for obtaining motion compensation, image synthesis and consistency observation. Significance of image-analysis algorithms in the context of object-oriented coding schemes; Representation of a framework for implementing CNN-based real-time image analysis; Confirmation of the validity of the approach.