Joint Hamming Coding for High Capacity Lossless Image Encryption and Embedding Scheme

doi:10.3390/app12041966

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/122356

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/122356

题名:	Joint Hamming Coding for High Capacity Lossless Image Encryption and Embedding Scheme
作者:	Chen, Yi-Hui;Lin, Pei-Yu;Wu, Hsin-Pei;Chen, Shih-Hsin
关键词:	reversible data embedding;privacy protection;privacy leakage;image encryption;hamming coding
日期:	2022-02-14
上传时间:	2022-03-04 12:12:36 (UTC+8)
出版者:	MDPI
摘要:	Encryption is a widely used solution to prevent privacy leakage and illegal spread when sensitive images are uploaded to cloud storage. Hiding technology also allows confidential data to be embedded into encrypted images for secret communication. As image accuracy without distortion is essential within certain fields (such as medicine and the military), sensitive images must be completely decrypted back into the original images. However, an encrypted image is a noise-like pattern that is meaningless to a user; thus, it is difficult for a user to find the accurate image they desire. Take keywords as search indexes and embed them in encrypted images for encrypted image retrieval as an example. This idea has been extended by Chen and Line’s scheme to achieve higher capacity with reversibility. The proposed scheme adjusts the coding results according to smooth and complex images to increase its hiding capacity. In addition, two thresholds are designed to adjust the predicted pixel value to be close to the original one. Experiments show that compared with the other schemes, the proposed method achieves superior results. In addition, a hidden encrypted image can be extracted from the cover image. Afterward, the hidden secrets can be completely extracted, and sensitive images can also be perfectly restored.
關聯:	Applied Sciences 12(4), 1966
DOI:	10.3390/app12041966
显示于类别:	[資訊工程學系暨研究所] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	73	检视/开启

在機構典藏中所有的数据项都受到原著作权保护.

TAIR相关文章

数据加载中.....