Skip navigation

Contourlet-DCT based multiple robust watermarkings for medical images

Contourlet-DCT based multiple robust watermarkings for medical images

Wu, Xiaoqi, Li, Jingbing ORCID: 0000-0002-2386-3728, Tu, Rong, Cheng, Jieren, Bhatti, Uzair Aslam and Ma, Jixin (2018) Contourlet-DCT based multiple robust watermarkings for medical images. Multimedia Tools and Applications, 78 (7). pp. 8463-8480. ISSN 1380-7501 (Print), 1573-7721 (Online) (doi:

[img] PDF (Published version)
24323 MA_Contourlet_DCT_Based_Multiple_Robust_Watermarkings_(Pub)_2018.pdf - Published Version
Restricted to Registered users only

Download (1MB) | Request a copy


In the current medical system, the privacy and security of the medical information with respect to its transmission and storage is a key challenge. In pursuit of this, we proposed a contourlet transform and Discrete Cosine Transform (DCT) based multiple robust watermarking algorithms for medical imaging. The proposed scheme uses contourlet transform to extract multidirectional and multiscale texture information, and then the DCT was used to acquire the feature vector in the low frequency directional subbands. Then we used Logistic Map to encrypt the watermark to ensure the security of the original watermarking information under a chaotic system. In watermark embedding and extraction phases, we adopted zero-watermarking technique to ensure the integrity of the medical images. Our experimental results show that the proposed algorithm can embed much more data with less complexity and dose not change the pixel value of the original image. Moreover, the proposed algorithm can extract the watermark effectively with good invisibility and robustness to common and geometric attacks.

Item Type: Article
Uncontrolled Keywords: Medical image, Contourlet-DCT, Zero watermarking, Robust
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Computer & Computational Science
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 26 Nov 2020 22:34
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 5
Selected for REF2021: None

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics