Preprint Article Version 1 This version is not peer-reviewed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 (doi: 10.20944/preprints201909.0232.v1). Long, J.; Zhu, L.; Yuan, X.; Sun, L. Efficient Multimedia Similarity Measurement Using Similar Elements. Preprints 2019, 2019090232 (doi: 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.

Subject Areas

image similarity; SMI; SMI temp index; PSMI

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