On the selection of optimal feature region set for robust digital image watermarking

Jen Sheng Tsai, Win Bin Huang, Yau Hwang Kuo

Research output: Contribution to journalArticlepeer-review

77 Citations (Scopus)

Abstract

A novel feature region selection method for robust digital image watermarking is proposed in this paper. This method aims to select a nonoverlapping feature region set, which has the greatest robustness against various attacks and can preserve image quality as much as possible after watermarked. It first performs a simulated attacking procedure using some predefined attacks to evaluate the robustness of every candidate feature region. According to the evaluation results, it then adopts a track-with-pruning procedure to search a minimal primary feature set which can resist the most predefined attacks. In order to enhance its resistance to undefined attacks under the constraint of preserving image quality, the primary feature set is then extended by adding into some auxiliary feature regions. This work is formulated as a multidimensional knapsack problem and solved by a genetic algorithm based approach. The experimental results for StirMark attacks on some benchmark images support our expectation that the primary feature set can resist all the predefined attacks and its extension can enhance the robustness against undefined attacks. Comparing with some well-known feature-based methods, the proposed method exhibits better performance in robust digital watermarking.

Original languageEnglish
Article number5565465
Pages (from-to)735-743
Number of pages9
JournalIEEE Transactions on Image Processing
Volume20
Issue number3
DOIs
Publication statusPublished - 2011 Mar

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

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