blind watermarking
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2021 ◽  
Vol 38 (6) ◽  
pp. 1637-1646
Author(s):  
KVSV Trinadh Reddy ◽  
S. Narayana Reddy

In distributed m-health communication, it is a major challenge to develop an efficient blind watermarking method to protect the confidential medical data of patients. This paper proposes an efficient blind watermarking for medical images, which boasts a very high embedding capacity, a good robustness, and a strong imperceptibility. Three techniques, namely, discrete cosine transform (DCT), Weber’s descriptors (WDs), and Arnold chaotic map, were integrated to our method. Specifically, the Arnold chaotic map was used to scramble the watermark image. Then, the medical image was partitioned into non-over lapping blocks, and each block was subjected to DCT. After that, the scrambled watermark image data were embedded in the middle-band DCT coefficients of each block, such that two bits were embedded in each block. Simulation results show that the proposed watermarking method provides better imperceptibility, robustness, and computational complexity results with higher embedding capacity than the contrastive method.


Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7845
Author(s):  
Mostafa M. Abdel-Aziz ◽  
Khalid M. Hosny ◽  
Nabil A. Lashin ◽  
Mostafa M. Fouda

This paper proposes a new blind, color image watermarking method using fast Walsh–Hadamard transformation (FWHT) and multi-channel fractional Legendre–Fourier moments (MFrLFMs). The input host color image is first split into 4 × 4 non-interfering blocks, and the MFrLFMs are computed for each block, where proper MFrLFMs coefficients are selected and FWHT is applied on the selected coefficients. The scrambled binary watermark has been inserted in the quantized selected MFrLFMs coefficients. The proposed method is a blind extraction, as the original host image is not required to extract the watermark. The proposed method is evaluated over many visual imperceptibility terms such as peak signal-to-noise ratio (PSNR), normalized correlation (NC), and bit error rate. The robustness of the proposed method is tested over several geometrical attacks such as scaling, rotation, cropping, and translation with different parameter values. The most widely recognized image processing attacks are also considered, e.g., compressing and adding noise attacks. A set of combination attacks are also tested to analyze the robustness of the proposed scheme versus several attacks. The proposed model’s experimental and numerical results for invisibility and robustness were superior to the results of similar watermarking methods.


Author(s):  
Khaldi Amine ◽  
Kahlessenane Fares ◽  
Kafi Med Redouane ◽  
Euschi Salah

In this work, we proposed a robust and blind watermarking approach to adequately secure medical images exchanged in telemedicine. This approach ensures the traceability and integrity of the medical and essential image for data security in the field of telemedicine. In this paper, a blind watermarking method is proposed to adequately secure the electronic patient records. The integration of the watermark will be carefully performed by combining the parity of the successive values. This innovative approach will be typically implemented in the three insertion domains: spatial, frequency and multi-resolution. For the spatial domain, the watermark will be integrated into the colorimetric values of the image. In the frequency domain, the watermark bits will be substituted to the DCT coefficient’s least significant bit. For the multi-resolution domain insertion, after calculating a DWT, the obtained LL sub-band coefficients will be used for the integration process. After comparing our approaches to the various recent works in the three domains, the obtained results demonstrate that our proposed approach offers a good imperceptibility for the frequency and spatial domains insertion.


2021 ◽  
Author(s):  
Chaoning Zhang ◽  
Adil Karjauv ◽  
Philipp Benz ◽  
In So Kweon
Keyword(s):  

2021 ◽  
Vol 24 (1) ◽  
pp. 67-80
Author(s):  
Abena Ndongo Hervé ◽  
Eloundou Ebassa Bertrand Ledoux ◽  
Bitjoka Laurent and Tieudjo Daniel
Keyword(s):  

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