KEYWORDS: Quantization, Digital watermarking, Error analysis, Distortion, Sensors, Modulation, Interference (communication), Signal detection, Information theory, Signal processing
Although quantization index modulation (QIM) schemes are optimal from an information theoretic capacity-maximization point of view, their robustness may be too restricted for widespread practical usage. Most papers assume that host signal samples are identically distributed from a single source distribution and therefore, they do not need to consider local adaptivity. In practice there may be however several reasons for introducing locally varying watermark parameters.
In this paper, we study how the Scalar Costa Scheme (which we take as a representative member of the class of QIM schemes) can be adapted to achieve practical levels of robustness and imperceptibility. We do this by choosing the basic watermark parameters on the basis of a perceptual model. An important aspect is the robustness of the statistic on which the adaptation rule is based. The detector needs to be able to accurately re-estimate the value of the parameters as used by the embedder, even in the presence of strong channel noise. One way to achieve this is to base the adaptation rule on an aggregate of the pixel values in a neighborhood around the relevant pixel. We present an analysis of the robustness-locality trade-off, based on a model for the bit error probability.
KEYWORDS: Video, Digital watermarking, Databases, Video compression, Image segmentation, Visualization, Error control coding, Video coding, Image processing, Data storage
This paper present the concept of robust video hashing as a tool for video identification. We present considerations and a technique for (i) extracting essential perceptual features from a moving image sequences and (ii) for identifying any sufficiently long unknown video segment by efficiently matching the hash value of the short segment with a large database of pre-computed hash values.
KEYWORDS: Digital watermarking, Databases, Error control coding, Information security, Video, Cell phones, Multimedia, Signal processing, Brain, Global system for mobile communications
Robust identification of audio, still images and video is currently almost always associated with watermarking. Although being a powerful tool, there are some relevant issues with the use of watermarking. In this paper we review these issues, and at the same time propose to reconsider the older technique of robust feature recognition as a serious alternative. Moreover, we argue that not only in the context of content recognition, but also for other applications, a benefit is to be expected from the combination of robust feature recognition and digital watermarking.
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