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Related Experiment Videos

Correlation filters with controlled scale response.

Ryan A Kerekes1, B V K Vijaya Kumar

  • 1Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA. rkerekes@andrew.cmu.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|July 13, 2006
PubMed
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New Minimum Average Correlation Energy Mellin Radial Harmonic (MACE-MRH) filters offer user-specified responses to scale distortion in image recognition. These filters improve discrimination and achieve sharp correlation peaks for enhanced location accuracy.

Area of Science:

  • Computer Vision
  • Pattern Recognition
  • Image Processing

Background:

  • Correlation filtering is vital for image recognition and location tasks.
  • Optimal tradeoff circular harmonic function filters address in-plane rotation distortion.
  • A need exists for filters that can manage scale distortion effectively.

Purpose of the Study:

  • Introduce a novel correlation filter design for user-specified responses to in-plane scale distortion.
  • Enhance discrimination capability in correlation filters.
  • Achieve sharp correlation peaks for improved accuracy in image recognition.

Main Methods:

  • Utilize the Mellin radial harmonic (MRH) transform.
  • Incorporate multiple harmonics into the correlation filter design.

Related Experiment Videos

  • Minimize average correlation energy (MACE) for sharp peaks, creating MACE-MRH filters.

    • Main Results:

    • Demonstrate a new MACE-MRH filter design method.
    • Present underlying theory for the MACE-MRH filter.
    • Showcase numerical simulation results validating the filter's performance.

    Conclusions:

    • MACE-MRH filters provide user-specified responses to scale distortion.
    • The proposed method enhances discrimination and correlation peak sharpness.
    • This advancement offers improved capabilities for image recognition and location.