期刊
NEUROCOMPUTING
卷 452, 期 -, 页码 675-689出版社
ELSEVIER
DOI: 10.1016/j.neucom.2020.07.139
关键词
Content-based image retrieval; Image representation; Database search; Computer vision; Big data; Deep learning
资金
- National Key R AMP
- D Program of China [2018YFC0808305]
With the advancement of Internet technology and digital devices, Content-Based Image Retrieval (CBIR) has rapidly developed and been widely applied. This paper surveyed the fast developments and applications of CBIR theories and algorithms from 2009 to 2019, focusing on technological advancements in image representation and database search, as well as practical applications in various fields.
With the development of Internet technology and the popularity of digital devices, Content-Based Image Retrieval (CBIR) has been quickly developed and applied in various fields related to computer vision and artificial intelligence. Currently, it is possible to retrieve related images effectively and efficiently from a large scale database with an input image. In the past ten years, great efforts have been made for new theories and models of CBIR and many effective CBIR algorithms have been established. In this paper, we present a survey on the fast developments and applications of CBIR theories and algorithms during the period from 2009 to 2019. We mainly review the technological developments from the viewpoint of image representation and database search. We further summarize the practical applications of CBIR in the fields of fashion image retrieval, person re-identification, e-commerce product retrieval, remote sensing image retrieval and trademark image retrieval. Finally, we discuss the future research directions of CBIR with the challenge of big data and the utilization of deep learning techniques.& nbsp; (c) 2020 Elsevier B.V. All rights reserved.
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