Soft Computing

, Volume 22, Issue 7, pp 2105–2120 | Cite as

Global similarity preserving hashing

Foundations
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Abstract

Hashing learning has attracted increasing attention these years with the explosive increase in data volume. Most existing hashing learning methods can be divided into two stages. Firstly, obtain low-dimensional representation of the original data. Secondly, quantize the low-dimensional representation of each sample and map them to binary codes. This two-stage hashing framework separates projection operation and quantization operation apart, and the original data structure cannot be well preserved after this kind of two-stage operation. Considering this, global similarity preserving hashing (GSPH) is proposed, which utilizes a joint hashing framework to directly project the original data to hamming space, and reduces the projection error and the quantization loss simultaneously. Moreover, GSPH presents a global similarity-based data sample reconstruction method, which describes the intrinsic manifold structure of original data more precisely. The image retrieval experimental results on Corel, CIFAR, LabelMe and NUS-WIDE datasets illustrate that our algorithm outperforms several other state-of-the-art methods.

Keywords

Hashing learning Joint hashing framework Manifold structure Image retrieval 

Notes

Acknowledgements

This study was funded by National Natural Science Foundation of Peoples Republic of China (61173163, 61370200, 61672130, 61602082) and China Postdoctoral Science Foundation (ZX20150629).

Compliance with ethical standards

Conflict of interest

Yang Liu, Lin Feng, Shenglan Liu and Muxin Sun declare that they have no conflict of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianChina
  2. 2.School of Innovation and EntrepreneurshipDalian University of TechnologyDalianChina

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