Dynamic content selection-And-prediction framework applied to reversible data hiding

Han Zhou Wu, Hong Xia Wang, Yun Qing Shi

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

13 Scopus citations

Abstract

The existing reversible data hiding (RDH) methods often use a fixed pixel preselection pattern and predictor to generate prediction errors that are then utilized for embedding secret data. According to Kerckhoffs's principle, this deterministic operation may allow an illegal decoder to successfully reconstruct the marked prediction-error histogram from a marked image, which is not desirable in application scenarios. This has prompted us to propose a dynamic content selection-And-prediction framework for the RDH in this paper. The proposed framework aims to auto-preselect the complex pixels out from a given image to predict the rest pixels that are thereafter exploited to carry the secret data. Comparing with some state-of-The-Art algorithms, the proposed technique guarantees that, the illegal decoder will hardly locate the whole marked pixels and determine the marked prediction errors, which can ensure the security level. In our designed framework, after pixel selection and prediction, there exists a lot of freedom to design the data embedding procedure, meaning that, the proposed framework can be applied to the design of an RDH scheme. In the experiments, we simply employ an optimized histogram shifting operation for data embedding after applying the proposed framework. Our experimental results have shown that, the data embedding process can benefit from the proposed pixel selection and prediction procedure with relatively low embedding rates, and therefore significantly outperform some related works in terms of the payload-distortion performance, especially for images with more smooth regions.

Original languageEnglish (US)
Title of host publication8th IEEE International Workshop on Information Forensics and Security, WIFS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509011384
DOIs
StatePublished - Jan 18 2017
Event8th IEEE International Workshop on Information Forensics and Security, WIFS 2016 - Abu Dhabi, United Arab Emirates
Duration: Dec 4 2016Dec 7 2016

Publication series

Name8th IEEE International Workshop on Information Forensics and Security, WIFS 2016

Other

Other8th IEEE International Workshop on Information Forensics and Security, WIFS 2016
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period12/4/1612/7/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Law

Keywords

  • Reversible data hiding (RDH)
  • dynamic
  • histogram shifting
  • multi-layer selection
  • prediction
  • watermarking

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