Web-scale System for Image Similarity Search: When the Dreams Are Coming True
| Authors | |
|---|---|
| Year of publication | 2008 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Sixth International Workshop on Content-Based Multimedia Indexing (CBMI 2008) |
| MU Faculty or unit | |
| Citation | |
| Web | http://index.ieeexplore.ieee.org/iel5/4558154/4564912/04564981.pdf |
| Field | Informatics |
| Keywords | similarity search; content-based search; image search; large-scale search; distributed data structures |
| Description | Digital images have become a commodity which is searched on the Web as ordinarily as web pages. However, current large-scale engines search the images only on the basis of their annotations, while the content-based similarity systems do not seem to be ready for such scales. In this paper, we open the way to Web-scale image similarity search. We present a flexible system based on the metric space model and on the peer-to-peer paradigm. It uses M-Chord and M-Tree structures as its fundamental components and measures the image similarity by a combination of five MPEG-7 features. The system has been implemented including a graphical interface for online demonstrations and it currently indexes 10 million images crawled from the Web. We propose a novel strategy for approximate evaluation of similarity queries and we test its performance by a series of experiments. The results show that the system provides high-quality answers with response times around 0.5 second. |
| Related projects: |