One-dimensional Fourier transform coefficients for rotation-invariant texture classification

Hamzah Arof; Farzin Deravi

doi:10.1117/12.257258

31 October 1996 One-dimensional Fourier transform coefficients for rotation invariant texture classification

Hamzah Arof, Farzin Deravi

Proceedings Volume 2908, Machine Vision Applications, Architectures, and Systems Integration V; (1996) https://doi.org/10.1117/12.257258
Event: Photonics East '96, 1996, Boston, MA, United States

Abstract

This paper introduces a texture descriptor that is invariant to rotation. The new texture descriptor utilizes the property of the magnitudes of Fourier transform coefficients that do not change with spatial shift of input elements. Since rotating an image by an arbitrary angle does not change pixel intensities in an image but shift them in circular motion, the notion of producing textural features invariant to rotation using 1D Fourier transform coefficients can be realized if the relationship between circular motion and spatial shift can be established. By analyzing pixels in a circular neighborhood in an image, a number of FOurier transform coefficients can be generated to describe local properties of the neighborhood. From the magnitudes of these coefficients, several rotation invariant features are obtained to represent each texture class. Based on these features, an unknown image is assigned to one of the known classes using a nearest neighbor classifier. All of the feature samples for the classifier are extracted from unrotated texture images only. The new texture descriptor outperformed the circular simultaneous autoregressive model in classifying rotated texture images taken from 30 texture classes.

Citation Download Citation

Hamzah Arof and Farzin Deravi "One-dimensional Fourier transform coefficients for rotation invariant texture classification", Proc. SPIE 2908, Machine Vision Applications, Architectures, and Systems Integration V, (31 October 1996); https://doi.org/10.1117/12.257258

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