Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2217-2223

Sparse difference network and multi-supervised hashing for efficient image retrieval

Zhang Zhisheng
Qu Huaijing
Xu Jia
Wang Jiwei
Wei Yanan
Xie Ming
Zhang Hanyuan
School of Information & Electric Engineering, Shandong Jianzhu University, Jinan 250101, China
DOI: 10.19734/j.issn.1001-3695.2021.11.0602

Abstract

In image retrieval based on deep hashing, to solve the problems of low feature extraction efficiency in convolutional neural networks(CNN) and underutilization of feature correlation, this paper proposed a novel method combining sparse difference network and multi-supervised hashing(SDNMSH), and used it for efficient image retrieval. SDNMSH took pairs of images as training inputs, and guided hash codes learning through an elaborately designed sparse difference convolutional neural network and a supervised hash function. The sparse difference convolutional layer and the vanilla convolutional layer composed the sparse difference convolutional neural network. The sparse difference convolutional layer could quickly extract rich feature information, to achieve efficient feature extraction of the entire network. At the same time, in order to make full use of the pairwise correlation of semantic information and features, so as to promote the feature information extracted by the network to be more effectively transformed into discriminative hash codes, and then to achieve efficient image retrieval by using SDNMSH, this paper adopted a multi-supervised hash(MSH) function and designed an objective function for this purpose. Extensive experimental results on three widely used datasets MNIST, CIFAR-10 and NUS-WIDE show that SDNMSH achieves better retrieval performance, compared with the state-of-the-arts.

Foundation Support

国家自然科学基金资助项目(62003191)
山东省自然科学基金资助项目(ZR2014FM016)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.11.0602
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Technology of Graphic & Image
Pages: 2217-2223
Serial Number: 1001-3695(2022)07-048-2217-07

Publish History

[2022-01-10] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

张志升, 曲怀敬, 徐佳, 等. 稀疏差分网络和多监督哈希用于高效图像检索 [J]. 计算机应用研究, 2022, 39 (7): 2217-2223. (Zhang Zhisheng, Qu Huaijing, Xu Jia, et al. Sparse difference network and multi-supervised hashing for efficient image retrieval [J]. Application Research of Computers, 2022, 39 (7): 2217-2223. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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