Scaling up the Image Content-based Retrieval
| Authors | |
|---|---|
| Year of publication | 2007 |
| Type | Article in Proceedings |
| Conference | Second DELOS Conference - Working Notes |
| MU Faculty or unit | |
| Citation | |
| Web | DELOS Network of Excellence |
| Field | Informatics |
| Keywords | similarity search; scalability; MPEG-7; image database |
| Description | The data-explosion phenomenon can be observed in two distinct respects: (1) The volume of data produced is increasing rapidly and (2) new data types appear and are widely used. This calls for development of brand new indexing and searching methods which would be efficient on huge amounts of data and respect the needs of the recent data types. This paper describes a transfer of our previous theoretical results into practice by building a fully functional application. The application is able to efficiently manage large collections of digital images and search these images according to their content. Its distributed architecture is based on the peer-to-peer paradigm and the searching method adopts the metric-based approach to similarity. Currently the application can store and search tens of millions of images crawled from the Web with dozens of simultaneous users, although it runs on a limited hardware infrastructure. |
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