Scalable image retrieval from distributed images database
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In order to store, and retrieve images from large databases, we propose a framework, based on multiple description coding paradigm, that disseminates images over distributed servers. Consequently, decentralized download can be performed, thus reducing links overload and hotspot areas without penalizing downloads speed. Moreover, the trade-off between system reliability and storage requirement can be achieved by tuning descriptions redundancy, thus providing high flexibility in terms of storage resources, reliability of access, and performance. The scalability of the proposed framework is achieved by the intrinsic progressivity of the multiple description schemes. Moreover, we demonstrate that system can work properly regardless of server crashes.