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Watermarking with retrieval systems
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AI
DOI：10.1007/s00530-003-0116-1.png)
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摘要
En 中文
We are interested in the problem of associating messages with multimedia content for the purpose of identifying them. This problem can be addressed by a watermarking system that embeds the associated messages into the multimedia content (also called Work). A drawback of watermarking is that the content will be distorted during embedding. On the other hand, if we assume that the database is available, the problem can be addressed by a retrieval system. Although no undesirable distortion is introduced when a retrieval system is used, the overhead of searching in large databases is fundamentally difficult (also known as the dimensionality curse). In this paper we present a novel framework that strikes a trade-off between watermarking and retrieval systems. Our framework avoids the dimensionality curse by introducing small distortions (watermark) into the multimedia content. From another perspective, the framework improves the watermarking performance, marked by significant reduction in distortion, by introducing searching ability in the message detection stage. To prove the concept, we give an algorithm based on the proposed notion of active clustering.
Keyword:
multimedia retrieval systems
multimedia security
watermarking
nearest-neighbor search
k-mean
