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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:
68U10Image processing (computing aspects)
94C10Switching theory, application of Boolean algebra; Boolean functions
37D99Dynamical systems with hyperbolic behavior
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References:
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