IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Roughness Classification with Aggregated Discrete Fourier Transform
Chao LIANGWenming YANGFei ZHOUQingmin LIAO
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2014 Volume E97.D Issue 10 Pages 2769-2779

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Abstract
In this paper, we propose a texture descriptor based on amplitude distribution and phase distribution of the discrete Fourier transform (DFT) of an image. One dimensional DFT is applied to all the rows and columns of an image. Histograms of the amplitudes and gradients of the phases between adjacent rows/columns are computed as the feature descriptor, which is called aggregated DFT (ADFT). ADFT can be easily combined with completed local binary pattern (CLBP). The combined feature captures both global and local information of the texture. ADFT is designed for isotropic textures and demonstrated to be effective for roughness classification of castings. Experimental results show that the amplitude part of ADFT is also discriminative in describing anisotropic textures and it can be used as a complementary descriptor of local texture descriptors such as CLBP.
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© 2014 The Institute of Electronics, Information and Communication Engineers
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