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Image annotation watermarking: nested object embedding using hypergraph model
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Source International Multimedia Conference archive
Proceedings of the 8th workshop on Multimedia and security table of contents
Geneva, Switzerland
SESSION: Applications II table of contents
Pages: 182 - 189  
Year of Publication: 2006
ISBN:1-59593-493-6
Authors
Claus Vielhauer  Otto-von-Guericke University, Magdeburg, Germany
Maik Schott  Otto-von-Guericke University, Magdeburg, Germany
Sponsors
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we introduce to the special domain of image annotation watermarking, based on embedding of hierarchical data related to objects into user-selected areas on an image. In comparison to earlier methods, the main goal of the work presented here is to provide a specific robustness, specifically against cropping, in a way that preserves hierarchical object relations even after retrieval from a partial image, which has been cut from the original (pure security aspects are of limited relevance for our application). We identify two initial categories for such relations, visual-functional and visual-spatial and suggest a novel coding scheme for the first of these. Our prototypical system consists of a new ontology-based interactive editor and a watermarking scheme, which is an extension of previously suggested block-based image watermarking towards the specific requirements for annotation watermarking. Our initial experiments of the new approach include evaluation of appropriate synchronization patterns and issues of their threshold-based exhaustive search. Further, we present results from robustness tests, which are based on cropping and lossy JPEG compression. Our findings show that the suggested method is capable to restore payload in a hierarchy-preserving way after up to 50% JPEG compression, with a low to medium loss of transparency, which has been evaluated subjectively. Further, we observe that even when limiting exhaustive search to those watermark candidates showing the highest embedding energy, we are able to correctly detect between 55% and 100% of cropped objects.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
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Collaborative Colleagues:
Claus Vielhauer: colleagues
Maik Schott: colleagues