A new watermarking method with obfuscated quasi-chirp transform

Kazuo Ohzeki, Yuanyu Wei, Yutaka Hirakawa, Kiyotsugu Sato

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

Watermark detection software is obfuscated using a table to hide embedding and detection algorithms. As the table size is limited, the block size is also limited for watermarking. To address this situation, a new quasi-chirp transform is developed to improve embedding efficiency. The quasi-chirp transform is different from the conventional DCT or Fourier transform. It contains multiple frequency components in a single basis of the transform. It disperses image data rather than compressing it, as the DCT does. The dispersed data increases the range for embedding watermarks. The chirp transform is able to embed even on a flat area of an image. Using this chirp transform, embedding and detection experiments for image data with small block sizes were carried out. A high SNR and robust watermark with an evaluated obfuscation were obtained.

元の言語English
ホスト出版物のタイトルDigital-Forensics and Watermarking - 10th International Workshop, IWDW 2011, Revised Selected Papers
ページ57-71
ページ数15
DOI
出版物ステータスPublished - 2012 9 7
イベント10th International Workshop on Digital-Forensics and Watermarking, IWDW 2011 - Atlantic City, NJ, United States
継続期間: 2011 10 232011 10 26

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7128 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

Conference

Conference10th International Workshop on Digital-Forensics and Watermarking, IWDW 2011
United States
Atlantic City, NJ
期間11/10/2311/10/26

    フィンガープリント

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Ohzeki, K., Wei, Y., Hirakawa, Y., & Sato, K. (2012). A new watermarking method with obfuscated quasi-chirp transform. : Digital-Forensics and Watermarking - 10th International Workshop, IWDW 2011, Revised Selected Papers (pp. 57-71). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 7128 LNCS). https://doi.org/10.1007/978-3-642-32205-1_7