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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 8
2284-2287

Hashing image retrieval based on bilinear iterative quantization

Cui Wencheng
Xu Panpan
Shao Hong
School of Information Science & Engineering, Shenyang University of Technology, Shenyang 110870, China
DOI: 10.19734/j.issn.1001-3695.2019.02.0066

Abstract

Iterative quantization hashing algorithm does not consider that most of high-dimensional visual descriptors for images exhibit a natural matrix structure. When high-dimensional feature vectors represented the visual descriptors and assigned long binary codes, a random projection matrix requires expensive complexities in both space and time. To address the above issues, this paper proposed a hashing image retrieval method based on bilinear iterative quantization, which mapped the high-dimensional into two smaller projection matrices using compact bilinear projections instead of a single large projection matrix. Then it minimized the quantization error in an iterative quantization way and generate effective hash code. Experiments on two datasets, CIFAR-10 and Caltech256. This method achieved comparable retrieval accuracy to the state-of-the-art 8 hashing methods while having orders of magnitude faster linear scanning time and smaller memory footprint. The results show that the proposed method can reduce the impact of the high dimensionality of data and improve the performance of ITQ, the algorithm can widely serve the hashing image retrieval application of high-dimensional data and long coded bits.

Foundation Support

国家自然科学基金资助项目(61372176)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.02.0066
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Algorithm Research & Explore
Pages: 2284-2287
Serial Number: 1001-3695(2020)08-008-2284-04

Publish History

[2020-08-05] Printed Article

Cite This Article

崔文成, 徐盼盼, 邵虹. 基于双线性迭代量化的哈希图像检索方法 [J]. 计算机应用研究, 2020, 37 (8): 2284-2287. (Cui Wencheng, Xu Panpan, Shao Hong. Hashing image retrieval based on bilinear iterative quantization [J]. Application Research of Computers, 2020, 37 (8): 2284-2287. )

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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