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High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
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Hierarchical representation of waveforms.

P V Sankar1, A Rosenfeld

  • 1Computer Science Center, University of Maryland, College Park, MD 20742.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel fuzzy connectedness approach for hierarchical waveform representation, offering an alternative to peak dominance methods. The research explores its potential for describing curves and images.

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Area of Science:

  • Signal processing
  • Image analysis
  • Computer vision

Background:

  • Hierarchical representation of waveforms is crucial for signal analysis.
  • Existing methods, such as peak dominance relations, have limitations.
  • Fuzzy connectedness offers a promising alternative framework.

Purpose of the Study:

  • To propose an alternative approach for hierarchical waveform representation using fuzzy connectedness.
  • To compare this new method with existing peak dominance relations.
  • To explore the extension of this approach to curve and image description.

Main Methods:

  • Utilizing concepts of fuzzy connectedness for waveform analysis.
  • Developing a hierarchical representation based on fuzzy connectivity.
  • Investigating the applicability to curve and image data.

Main Results:

  • Demonstrated a viable alternative to peak dominance for hierarchical waveform representation.
  • Showcased the flexibility of fuzzy connectedness in capturing waveform structures.
  • Identified potential for extension to broader data types.

Conclusions:

  • Fuzzy connectedness provides a robust framework for hierarchical waveform representation.
  • The proposed method offers advantages in certain applications.
  • Further research can extend its utility to image and curve analysis.