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Fourier and Wavelet Analysis for Particle Shape and Texture Characterization

Many descriptors and methods have been developed to characterize shapes. Common ones such as aspect ratio, equivalent spherical diameter, and symmetry reveal valuable information about the shapes being studied. However, the complex nature of orthopedic wear particles limits the capabilities of such simple descriptors.

In order to effectively characterize wear particles with complex and reentrant boundaries, Discrete Fourier Transform (DFT) method has been investigated and applied. Traditionally used in signal processing, DFT treats the particle boundaries as periodic signals, and reveals information about general shape as well as fine textural details. A series of algorithms involving image processing have been developed using MATLAB to obtain normalized Fourier Descriptors that are invariant to translation, rotation, and scaling. Such descriptors can be used in future classification schemes.

Currently we are also developing algorithms to apply Harmonic Wavelet Transform in analyzing the roughness of particle contours.

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