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Image-processing algorithms realized by discrete-time cellular neural networks and their circuit implementations. (English) Zbl 1142.68575
Summary: In this study, eight image tasks: connected component detection (CCD) with down, right, $$+45^{\circ}$$ and $$-45^{\circ}$$ directions, edge detection, shadow projection with left and right directions and point removal are analyzed. These tasks are solved using the binary input and binary output discrete-time cellular neural networks (DTCNNs) associated with suitable templates. Furthermore, the behavior of the DTCNNs can be realized using Boolean functions, and the corresponding equivalent logic circuits are derived. An $$8 \times 8$$ DTCNNs-based image-processing chip is implemented by the FPGA technology. A simulation of the chip developed for the CCD task is also presented.

MSC:
 68U10 Computing methodologies for image processing 94C10 Switching theory, application of Boolean algebra; Boolean functions (MSC2010) 37D99 Dynamical systems with hyperbolic behavior
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References:
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