Improved differential energy watermarking for embedding watermark

Goo Rak Kwon, Seung Won Jung, Sang Jae Nam, Sung Jea Ko

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

Abstract

Digital watermarking is increasingly demanded for protecting or verifying the original image ownership. In this paper, we propose an improved differential energy watermarking using adaptive differential energy watermarking (ADEW) with cross binding wavelet tree (CBWT). The ADEW embeds a secret bit string which is obtained by the error correction code (ECC). Thus, the proposed method not only takes advantage of the ADEW's error resilience but corrects a secret bit string by using ECC after error occurrence. Through experiments, we compare the proposed method with conventional DEW approaches and the proposed method shows the appropriateness for robust watermarking.

Original languageEnglish
Title of host publicationDigital Watermarking - 5th International Workshop, IWDW 2006, Proceedings
PublisherSpringer Verlag
Pages377-386
Number of pages10
ISBN (Print)3540488251, 9783540488255
DOIs
Publication statusPublished - 2006
Event5th International Workshop on Digital Watermarking, IWDW 2006 - Jeju Island, Korea, Republic of
Duration: 2006 Nov 82006 Nov 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4283 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Workshop on Digital Watermarking, IWDW 2006
CountryKorea, Republic of
CityJeju Island
Period06/11/806/11/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kwon, G. R., Jung, S. W., Nam, S. J., & Ko, S. J. (2006). Improved differential energy watermarking for embedding watermark. In Digital Watermarking - 5th International Workshop, IWDW 2006, Proceedings (pp. 377-386). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4283 LNCS). Springer Verlag. https://doi.org/10.1007/11922841_30