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Multi-scale counting and difference representation for texture classification

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Abstract

Multi-scale analysis has been widely used for constructing texture descriptors by modeling the coefficients in transformed domains. However, the resulting descriptors are not robust to the rotated textures when performing texture classification. To alleviate this problem, we in this paper propose a multi-scale counting and difference representation (CDR) of image textures for texture classification. Particularly, we first extract a single-scale CDR feature consisting of the local counting vector (LCV) and the differential excitation vector (DEV). The LCV is established to capture different types of textural structures using the discrete local counting projection, while the DEV is used to describe the difference information of textures in accordance with the differential excitation projection. Finally, the multi-scale CDR feature of a texture image is constructed by combining CDRs at different scales. Experimental results on Brodatz, VisTex, and Outex databases demonstrate that our proposed multi-scale CDR-based texture classification method outperforms five representative texture classification methods.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant U1604153, and in part by the International Science and Technology Cooperation Project of Henan Province under Grant 162102410021.

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Authors and Affiliations

  1. School of Information Engineering, Henan University of Science and Technology, 263, Kaiyuan Avenue, Luoyang, 471023, People’s Republic of China

    Yongsheng Dong, Jinwang Feng, Chunlei Yang, Xiaohong Wang, Lintao Zheng & Jiexin Pu

  2. Department of Software Engineering, Zhengzhou Technical College, 81, Zhengshang Road, Zhengzhou, 450121, People’s Republic of China

    Jinwang Feng

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  1. Yongsheng Dong
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  2. Jinwang Feng
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  3. Chunlei Yang
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  4. Xiaohong Wang
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  5. Lintao Zheng
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  6. Jiexin Pu
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Correspondence to Jinwang Feng.

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Dong, Y., Feng, J., Yang, C. et al. Multi-scale counting and difference representation for texture classification. Vis Comput 34, 1315–1324 (2018). https://doi.org/10.1007/s00371-017-1415-4

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