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Circular-Fourier-radial-Mellin transform descriptors for pattern recognition.

Y Sheng, J Duvernoy

Journal of the Optical Society of America. A, Optics and Image Science

|June 1, 1986

Summary

New image descriptors using a circular-Fourier-radial-Mellin transform offer invariance to rotation, scale, and translation. This generalized approach enhances image analysis and can be computed in real-time using optical processors.

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Area of Science:

Computer Vision
Image Processing
Pattern Recognition

Background:

Traditional image descriptors often lack invariance to geometric transformations.
Existing methods like circular-harmonic expansion and moment invariants have limitations.

Purpose of the Study:

To propose novel image descriptors invariant to rotation, translation, and scale changes.
To present a generalized framework encompassing various existing descriptor types.

Main Methods:

Development of descriptors based on the circular-Fourier-radial-Mellin transform.
Mathematical formulation generalizing circular-harmonic expansion, Mellin transform, and moment invariants.

Main Results:

The proposed descriptors demonstrate invariance to rotation, translation, and scale.

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A unified approach is established, integrating multiple descriptor techniques.

Conclusions:

The circular-Fourier-radial-Mellin transform provides a robust method for creating invariant image descriptors.
The potential for real-time computation using optical processors is highlighted for practical applications.