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Multi-trend binary code descriptor: a novel local texture feature descriptor for image retrieval

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Abstract

With the development of image vision technology, local descriptors have attracted wide attention in the fields of image retrieval and classification. Even though varieties of methods based on local descriptor have achieved excellent performance, most of them cannot effectively represent the trend of pixels change, and they neglect the mutual occurrence of patterns. Therefore, how to construct local descriptors is of vital importance but challenging. In order to solve this problem, this paper proposes a multi-trend binary code descriptor (MTBCD). MTBCD mimics the visual perception of human to describe images by constructing a set of multi-trend descriptors which are encoded with binary codes. The method exploits the trend of pixels change in four symmetric directions to obtain the texture feature, and extracts the spatial correlation information using co-occurrence matrix. These intermediate features are integrated into one histogram using a new fusion strategy. The proposed method not only captures the global color features, but also reflects the local texture information. Extensive experiments have demonstrated the excellent performance of the proposed method.

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Notes

  1. The code and specified parameter files are provided here: http://www.vlfeat.org/matconvnet/pretrained/.

  2. https://github.com/willard-yuan/CNN-for-Image-Retrieval.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (Nos. 61173163, 61370200, 61672130, 61602082). The authors would like to thank the anonymous reviewers for their comments.

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Authors and Affiliations

  1. School of Computer Science and Technology, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China

    Laihang Yu, Lin Feng, Huibing Wang, Li Li & Yang Liu

  2. School of Innovation and Entrepreneurship of DUT, Dalian, 116024, China

    Lin Feng & Shenglan Liu

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  1. Laihang Yu
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  2. Lin Feng
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  3. Huibing Wang
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  4. Li Li
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  5. Yang Liu
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  6. Shenglan Liu
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Correspondence to Lin Feng.

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Yu, L., Feng, L., Wang, H. et al. Multi-trend binary code descriptor: a novel local texture feature descriptor for image retrieval. SIViP 12, 247–254 (2018). https://doi.org/10.1007/s11760-017-1152-1

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  • DOI: https://doi.org/10.1007/s11760-017-1152-1

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