  Online social networking techniques and large-scale multimedia systems are
developing rapidly, which not only has brought great convenience to our daily
life, but generated, collected, and stored large-scale multimedia data. This
trend has put forward higher requirements and greater challenges on massive
multimedia data retrieval. In this paper, we investigate the problem of image
similarity measurement which is used to lots of applications. At first we
propose the definition of similarity measurement of images and the related
notions. Based on it we present a novel basic method of similarity measurement
named SMIN. To improve the performance of calculation, we propose a novel
indexing structure called SMI Temp Index (SMII for short). Besides, 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 our solution outperforms state-of-the-art
method.
