Data hiding in a hologram by modified digital halftoning techniques

Hsi Chun Wang, Wei Chiang Wang

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

2 Citations (Scopus)

Abstract

The objective of this research is to design a novel data hiding method for the dot-matrix hologram. The modified error diffusion techniques for addressing the halftone dots in six colors are proposed to make efficient use of the image area and to hide information. After outputting the encoded hologram, which is in analog format, an independent data recovery system is applied to capture the encoded holographic image and to extract the hidden information. The results show that it is feasible to hide data in a dot-matrix hologram. The method proposed in this research can achieve multiple security features for hologram in anti-counterfeiting applications.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
Pages1086-1092
Number of pages7
Publication statusPublished - 2005 Dec 1
Event9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
Duration: 2005 Sep 142005 Sep 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3683 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
CountryAustralia
CityMelbourne
Period05/9/1405/9/16

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Wang, H. C., & Wang, W. C. (2005). Data hiding in a hologram by modified digital halftoning techniques. In Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings (pp. 1086-1092). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3683 LNAI).