A DWT-DFT Composite Watermarking Scheme Robust to Both Affine Transform and JPEG Compression

Document Type

Article

Publication Date

8-1-2003

Abstract

Robustness is one of the crucial important issues in watermarking. Robustness against geometric distortion and JPEG compression at the same time with blind extraction remains especially challenging. In this paper, a blind discrete wavelet transform-discrete Fourier transform (DWT-DFT) composite image watermarking algorithm that is robust against both affine transformation and JPEG compression is proposed. This algorithm Improves the robustness via using new embedding strategy, watermark structure, 2-D Interleaving, and synchronization technique. A spread-spectrum-based informative watermark with a training sequence are embedded in the coefficients of the LL subband in the DWT domain while a template is embedded in the middle frequency components in the DFT domain. In watermark extraction, we first detect the template in a possibly corrupted watermarked image to obtain the parameters of affine transform and convert the image back to its original shape. Then we perform translation registration by using the training sequence embedded in the DWT domain and finally extract the informative watermark. Experimental works have demonstrated that the watermark generated by the proposed algorithm is more robust than other watermarking algorithms reported in the literature. Specifically it is robust against almost all affine transform related testing functions in StirMark 3.1 and JPEG compression with quality factor as low as 10 simultaneously. While the approach is presented for gray-level images, it can also be applied to color images and video sequences.

Identifier

0141638482 (Scopus)

Publication Title

IEEE Transactions on Circuits and Systems for Video Technology

External Full Text Location

https://doi.org/10.1109/TCSVT.2003.815957

ISSN

10518215

First Page

776

Last Page

786

Issue

8

Volume

13

Grant

013164

Fund Ref

National Science Foundation

This document is currently not available here.

Share

COinS