Damageless watermark extraction using nonlinear feature extraction scheme trained on frequency domain

Kensuke Naoe, Yoshiyasu Takefuji

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this chapter, we propose a new information hiding and extracting method without embedding any information into the target content by using a nonlinear feature extraction scheme trained on frequency domain. The proposed method can detect hidden bit patterns from the content by processing the coefficients of the selected feature subblocks to the trained neural network. The coefficients are taken from the frequency domain of the decomposed target content by frequency transform. The bit patterns are retrieved from the network only with the proper extraction keys provided. The extraction keys, in the proposed method, are the coordinates of the selected feature subblocks and the neural network weights generated by the supervised learning of the neural network. The supervised learning uses the coefficients of the selected feature subblocks as the set of input values, and the hidden bit patterns are used as the teacher signal values of the neural network, which is the watermark signal in the proposed method. With our proposed method, we are able to introduce a watermark scheme with no damage to the target content.

Original languageEnglish
Title of host publicationIntellectual Property Protection for Multimedia Information Technology
PublisherIGI Global
Pages117-142
Number of pages26
ISBN (Print)9781599047621
DOIs
Publication statusPublished - 2007 Dec 1

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Naoe, K., & Takefuji, Y. (2007). Damageless watermark extraction using nonlinear feature extraction scheme trained on frequency domain. In Intellectual Property Protection for Multimedia Information Technology (pp. 117-142). IGI Global. https://doi.org/10.4018/978-1-59904-762-1.ch005