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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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