New wavelet-based scheme for watermarking images

Rakesh Dugad, Krishna Ratakonda, Narendra Ahuja

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

Abstract

A new method for digital image watermarking which does not require the original image for watermark detection is presented. Assuming that we are using a transform domain spread spectrum watermarking scheme, it is important to add the watermark in select coefficients with significant image energy in the transform domain in order to ensure non-erasability of the watermark. Previous methods, which did not use the original in the detection process, could not selectively add the watermark to the significant coefficients, since the locations of such selected coefficients can change due to image manipulations. Since watermark verification typically consists of a process of correlation which is extremely sensitive to the relative order in which the watermark coefficients are placed within the image, such changes in the location of the watermarked coefficients was unacceptable. We present a scheme which overcomes this problem of 'order sensitivity'. Advantages of the proposed method include (i) improved resistance to attacks on the watermark, (ii) implicit visual masking utilizing the time-frequency localization property of the wavelet transform and (iii) a robust definition for the threshold which validates the watermark. We present results comparing our method with previous techniques, which clearly validate our claims.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE Comp Soc
Pages419-421
Number of pages3
Volume2
StatePublished - 1998
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: Oct 4 1998Oct 7 1998

Other

OtherProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period10/4/9810/7/98

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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