Adaptive decoding for halftone orientation-based data hiding

Orhan Bulan, Gaurav Sharma, Vishal Monga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Halftone image watermarking techniques that allow automated extraction of the embedded watermark data are useful in a variety of document security and workflow applications. The print-scan process inherent in these applications introduces distortions whose characteristics exhibit a strong spatial dependence on the cover image in which the data is embedded. In this paper, we demonstrate that a characterization of this channel dependence and the use of error correction coding that exploits this dependence via image adaptive decoding offers a significant performance gain. We show this advantage in the specific context of a high rate data embedding method that utilizes orientation modulation for data embedding in clustered dot halftones and moment based detection at the receiver. Channel coding for this scenario utilizing convolutional codes and Repeat Accumulate (RA) codes highlights the advantage of the proposed adaptive decoding methodology. The performance for the RA codes with adaptive decoding also reveals that the resulting system has significantly higher operational rates than prior schemes.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages1280-1283
Number of pages4
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: Oct 12 2008Oct 15 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2008 IEEE International Conference on Image Processing, ICIP 2008
CountryUnited States
CitySan Diego, CA
Period10/12/0810/15/08

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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