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Memristive fuzzy edge detector

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Abstract

Fuzzy inference systems always suffer from the lack of efficient structures or platforms for their hardware implementation. In this paper, we tried to overcome this difficulty by proposing a new method for the implementation of the fuzzy rule-based inference systems. To achieve this goal, we have designed a multi-layer neuro-fuzzy computing system based on the memristor crossbar structure by introducing a new concept called the fuzzy minterm. Although many applications can be realized through the use of our proposed system, in this study we only show how the fuzzy XOR function can be constructed and how it can be used to extract edges from grayscale images. One main advantage of our memristive fuzzy edge detector (implemented in analog form) compared to other commonly used edge detectors is it can be implemented in parallel form, which makes it a powerful device for real-time applications.

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Acknowledgments

The authors thank the anonymous reviewers for suggesting many useful comments to improve the quality of this work.

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Authors and Affiliations

  1. Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran

    Farnood Merrikh-Bayat & Saeed Bagheri Shouraki

  2. Department of Electrical and Computer Engineering, University of Zanjan, Zanjan, Iran

    Farshad Merrikh-Bayat

Authors
  1. Farnood Merrikh-Bayat
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  2. Saeed Bagheri Shouraki
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  3. Farshad Merrikh-Bayat
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Correspondence to Farnood Merrikh-Bayat.

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Merrikh-Bayat, F., Bagheri Shouraki, S. & Merrikh-Bayat, F. Memristive fuzzy edge detector. J Real-Time Image Proc 9, 479–489 (2014). https://doi.org/10.1007/s11554-012-0254-9

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