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Image analysis using hahn moments.

Pew-Thian Yap1, Raveendran Paramesran, Seng-Huat Ong

  • 1School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798. pewthian@ntu.edu.sg

IEEE Transactions on Pattern Analysis and Machine Intelligence
|September 13, 2007
PubMed
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Hahn moments unify Chebyshev and Krawtchouk moments, offering a generalized approach for feature extraction and analysis of complex signals. This unified framework enhances understanding and application in signal processing.

Area of Science:

  • Digital Signal Processing
  • Image Analysis
  • Mathematical Physics

Background:

  • Chebyshev and Krawtchouk moments are established methods for image analysis.
  • A need exists for a unified mathematical framework to encompass these and related moment descriptors.
  • Understanding the properties and applications of generalized moment functions is crucial for advanced signal processing.

Purpose of the Study:

  • To demonstrate that Hahn moments generalize Chebyshev and Krawtchouk moments.
  • To explore the application of Hahn moments for both global and local feature extraction.
  • To integrate Hahn moments with normalized convolution for analyzing irregularly sampled signals.

Main Methods:

  • Derivation of Chebyshev and Krawtchouk moments as special cases of Hahn moments.

Related Experiment Videos

  • Application of Hahn moments for feature extraction in digital signals.
  • Incorporation of Hahn moments into the normalized convolution framework.

    • Main Results:

    • Hahn moments provide a unified theoretical basis for Chebyshev and Krawtchouk moments.
    • Demonstrated effectiveness of Hahn moments in global and local feature extraction.
    • Successful application of Hahn moments within normalized convolution for analyzing complex signal structures.

    Conclusions:

    • Hahn moments offer a comprehensive and unified approach to moment-based signal analysis.
    • The generalized framework of Hahn moments expands capabilities in feature extraction and signal structure analysis.
    • This work facilitates advanced analysis of irregularly sampled signals using a unified moment theory.