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BHoG: binary descriptor for sketch-based image retrieval

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Abstract

Due to the popularity of devices with touch screens, it is convenient to match images with a hand-drawn sketch query. However, existing methods usually care little about memory space and time efficiency thus is inadequate for the rapid growth of multimedia resources. In this paper, a BHoG descriptor is proposed for sketch-based image retrieval. Firstly, the boundary image is detected from natural image using Berkeley boundary detector, and then divided into many blocks. Secondly, we calculate the gradient feature of each block, and find the principal gradient orientation. Finally, the principal gradient orientation is encoded to binary codes, which is proved to be efficient and discriminative. We evaluated the performance of BHoG on a large-scale social media dataset. The experimental results have shown that BHoG not only has a better performance on flexibility and efficiency, but also occupies small memory.

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Acknowledgments

The work is supported by the Fundamental Research Funds for the Central Universities DUT14QY03.

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Authors and Affiliations

  1. School of Information and Communication Engineering, Dalian University of Technology, Dalian, 116023, China

    Haiyan Fu, Hanguang Zhao, Xiangwei Kong & Xianbo Zhang

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  1. Haiyan Fu
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  2. Hanguang Zhao
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  3. Xiangwei Kong
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  4. Xianbo Zhang
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Correspondence to Xiangwei Kong.

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Fu, H., Zhao, H., Kong, X. et al. BHoG: binary descriptor for sketch-based image retrieval. Multimedia Systems 22, 127–136 (2016). https://doi.org/10.1007/s00530-014-0406-9

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  • DOI: https://doi.org/10.1007/s00530-014-0406-9

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