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Multimedia Tools and Applications

, Volume 78, Issue 1, pp 661–676 | Cite as

Supervised deep hashing for image content security

  • Yanping Ma
  • Dongbao YangEmail author
  • Hongtao XieEmail author
  • Jian Yin
Article
  • 112 Downloads

Abstract

Due to the fast growth of image data on the web, it is necessary to ensure the content security of uploaded images. One of the fundamental problems behind this need is retrieving relevant images from the large-scale databases. Recently, hashing/binary coding algorithms have proved to be effective for large-scale visual information retrieval. Most existing hashing methods usually seek single linear projections to map each sample into a binary vector. In this paper, a supervised deep hashing method is proposed, which seeks multiple non-linear transformations to generate more discriminative binary codes with short bits. We implement a deep Convolutional Neural Network to achieve end-to-end hashing. A loss function is elaborately devised to preserve the similarity relationship between images, meanwhile minimize the quantization error and make hash bits distribute evenly. Extensive experimental comparisons with state-of-the-art hashing algorithms are conducted on CIFAR-10 and NUS-WIDE, the MAP reaches to 87.67% and 77.48% with 48 bits respectively. It shows that the proposed method achieves very competitive results with the state-of-the-arts.

Keywords

Image content security Hashing Binary codes Deep learning 

Notes

Acknowledgements

This work is supported by the National Nature Science Foundation of China (61771468), the Youth Innovation Promotion Association Chinese Academy of Sciences (2017209). Thanks to the contributions made by Yan Li from Beijing Kuaishou Technology Co., Ltd., who has examined the whole manuscript with respect to the usages of verb tense, singular and plural forms of nouns, and articles and has also conducted some experiments.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Information and Electrical EngineeringLudong UniversityYantaiChina
  2. 2.School of Mechanical, Electrical and Information EngineeringShandong UniversityWeihaiChina
  3. 3.School of Information Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina

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