Image-processing algorithms realized by discrete-time cellular neural networks and their circuit implementations

Hsin-Chieh Chen, Yung-Ching Hung, Chang-Kuo Chen, Teh-Lu Liao and Chun-Kuo Chen

Chaos, Solitons & Fractals, 2006, vol. 29, issue 5, 1100-1108

Abstract: In this study, eight image tasks: connected component detection (CCD) with down, right, +45° and −45° 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 8×8 DTCNNs-based image-processing chip is implemented by the FPGA technology. A simulation of the chip developed for the CCD task is also presented.

Date: 2006
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:29:y:2006:i:5:p:1100-1108

DOI: 10.1016/j.chaos.2005.08.067

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