Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 10
3186-3193,3200

Object saliency ranking awareness network for efficient image retrieval

Li Linfeng1
Chen Chenglizhao2
Wang Hengsen1
1. College of Computer Science & Technology, Qingdao University, Qingdao Shandong 266071, China
2. College of Computer Science & Technology, China Petroleum University, Qingdao Shandong 266580, China
DOI: 10.19734/j.issn.1001-3695.2023.01.0028

Abstract

This paper introduced a novel approach for image retrieval, the scene-aware object saliency ranking algorithm(SASR), which addressed the issue of traditional image retrieval techniques relying on semantic similarity and neglecting the crucial importance of object relationships within a scene. SASR consisted of two stages. In the first stage, this paper proposed a viewpoint data-based method called the "combined threshold" to annotate true value labels for object-level saliency ranking, simplifying the annotation of ranking labels. In the second stage, this paper presented an object-level saliency ranking network based on graph convolutional networks that resolved several specific difficulties encountered in sorting objects. The proposed algorithm improved on the current saliency ranking label generation methods and was tested via a large number of comparative experiments. The experimental results on the SALICON dataset show that the SASR algorithm enhances saliency ranking performance significantly. Moreover, the results from the NUS-WIDE dataset indicate that, when supported by the proposed algorithm, image retrieval performance increases by an average of 2%, which solidifies the efficacy of the proposed algorithm.

Foundation Support

山东省高等学校青创科技计划创新团队资助项目(2021KJ062)
国家自然科学基金资助项目(61802215)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.01.0028
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 10
Section: Technology of Graphic & Image
Pages: 3186-3193,3200
Serial Number: 1001-3695(2023)10-047-3186-08

Publish History

[2023-04-25] Accepted Paper
[2023-10-05] Printed Article

Cite This Article

李林峰, 陈程立诏, 王恒森. 物体显著性排名感知网络用于高效图像检索 [J]. 计算机应用研究, 2023, 40 (10): 3186-3193,3200. (Li Linfeng, Chen Chenglizhao, Wang Hengsen. Object saliency ranking awareness network for efficient image retrieval [J]. Application Research of Computers, 2023, 40 (10): 3186-3193,3200. )

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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