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In this paper, we present a novel scalable logo recognition system which can recognize a large number of logo categories locally on mobile devices. The system is unsupervised without any supervised training procedure, and very time efficient at low memory cost. It is also robust against challenging conditions such as noise addition, different image scale, rotation, etc. To achieve this goal, we propose...
This paper proposes a novel data embedding method for embedding secrets into VQ indices by using the Chinese Remainder Theorem (CRT). In the experimental results, the hiding capacity is flexible which corresponds to the pre-defined prime parameters. In addition, a reversible mechanism is imported into the scheme so the original VQ indices can be restored after extracting secrets retrieval.
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