Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Efficient Multimedia Similarity Measurement Using Similar Elements

Version 1 : Received: 19 September 2019 / Approved: 20 September 2019 / Online: 20 September 2019 (05:32:21 CEST)

How to cite: Long, J.; Zhu, L.; Yuan, X.; Sun, L. Efficient Multimedia Similarity Measurement Using Similar Elements. Preprints 2019, 2019090232. https://doi.org/10.20944/preprints201909.0232.v1 Long, J.; Zhu, L.; Yuan, X.; Sun, L. Efficient Multimedia Similarity Measurement Using Similar Elements. Preprints 2019, 2019090232. https://doi.org/10.20944/preprints201909.0232.v1

Abstract

Online social networking techniques and large-scale multimedia retrieval are developing rapidly, which not only has brought great convenience to our daily life, but generated, collected, and stored large-scale multimedia data as well. This trend has put forward higher requirements and greater challenges on massive multimedia retrieval. In this paper, we investigate the problem of image similarity measurement, which is one of the key problems of multimedia retrieval. Firstly, the definition of similarity measurement of images and the related notions are proposed. Then, an efficient similarity measurement framework is proposed. Besides, we present a novel basic method of similarity measurement named SMIN. To improve the performance of similarity measurement, we carefully design a novel indexing structure called SMI Temp Index (SMII for short). Moreover, we establish an index of potential similar visual words off-line to solve to problem that the index cannot be reused. Experimental evaluations on two real image datasets demonstrate that the proposed approach outperforms state-of-the-arts.

Keywords

image similarity; SMI; SMI temp index; PSMI

Subject

Computer Science and Mathematics, Information Systems

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.