Reversible watermarking for medical images using histogram shifting with location map reduction

Nai Kuei Chen, Chung-Yen Su, Che Yang Shih, Yu Tang Chen

研究成果: 書貢獻/報告類型會議貢獻

7 引文 斯高帕斯(Scopus)

摘要

In this paper, an improved lossless data hiding method with histogram shifting for medical images is proposed. In general, medical images consist of many pure black and white points. In the previous studies, it may need a lot of data as a location map to reconstruct the watermark and the cover image. To solve this problem, we present a new method to record the location map. We use two bits for each block to record the information of histogram shifting and one bit to denote the change of each pixel value on the cover image. The purpose of the former two bits is to avoid wrong information in the extracting process, while that of the latter one is to avoid overflow and underflow. Experimental results show that our method can reduce the size of location map up to 95.04% compared to the previous studies.

原文英語
主出版物標題Proceedings - 2016 IEEE International Conference on Industrial Technology, ICIT 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面792-797
頁數6
ISBN(電子)9781467380751
DOIs
出版狀態已發佈 - 2016 五月 19
事件IEEE International Conference on Industrial Technology, ICIT 2016 - Taipei, 臺灣
持續時間: 2016 三月 142016 三月 17

出版系列

名字Proceedings of the IEEE International Conference on Industrial Technology
2016-May

其他

其他IEEE International Conference on Industrial Technology, ICIT 2016
國家臺灣
城市Taipei
期間16/3/1416/3/17

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • 引用此

    Chen, N. K., Su, C-Y., Shih, C. Y., & Chen, Y. T. (2016). Reversible watermarking for medical images using histogram shifting with location map reduction. 於 Proceedings - 2016 IEEE International Conference on Industrial Technology, ICIT 2016 (頁 792-797). [7474852] (Proceedings of the IEEE International Conference on Industrial Technology; 卷 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIT.2016.7474852