Rotation Invariant Texture Analysis Using Radon and Fractional Fourier Transform

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Fakhordin Mohammadi Junbin Gao Daming Shi

Abstract

In this paper we propose a new rotation invariant feature descriptor for texture classification and clustering via first identifying the so-called principal direction of textures with the well-known Radon transform and then extracting features defined by the fractional Fourier transform of different order from the rotated textures along their principal direction. The performance of the proposed method is evaluated using different kind of texture sets. Results show the advantage of the proposed method over some existing algorithms.

Article Details

How to Cite
MOHAMMADI, Fakhordin; GAO, Junbin; SHI, Daming. Rotation Invariant Texture Analysis Using Radon and Fractional Fourier Transform. INFOCOMP, [S.l.], v. 13, n. 2, p. 1-9, dec. 2014. ISSN 1982-3363. Available at: <http://infocomp.dcc.ufla.br/index.php/INFOCOMP/article/view/390>. Date accessed: 16 dec. 2017.
Keywords
Texture classification, Radon transform, Fractional Fourier transform, Rotation invariant.
Section
Articles