Saima Kanwal¹, Feng Tao^1,*, Ahmad Almogren², Ateeq Ur Rehman³, Rizwan Taj¹, Ayman Radwan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 201-219, 2023, DOI:10.32604/cmes.2022.020255

Abstract The authenticity and integrity of healthcare is the primary objective. Numerous reversible watermarking schemes have been developed to improve the primary objective but increasing the quantity of embedding data leads to covering image distortion and visual quality resulting in data security detection. A trade-off between robustness, imperceptibility, and embedded capacity is difficult to achieve with current algorithms due to limitations in their ability. Keeping this purpose insight, an improved reversibility watermarking methodology is proposed to maximize data embedding capacity and imperceptibility while maintaining data security as a primary concern. A key is generated by a random path with minimum bit… More >

Rizwan Taj¹, Feng Tao^1,*, Shahzada Khurram², Ateeq Ur Rehman³, Syed Kamran Haider⁴, Akber Abid Gardezi⁵, Saima Kanwal¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1309-1324, 2022, DOI:10.32604/cmes.2022.017650

Abstract In telemedicine, the realization of reversible watermarking through information security is an emerging research field. However, adding watermarks hinders the distribution of pixels in the cover image because it creates distortions (which lead to an increase in the detection probability). In this article, we introduce a reversible watermarking method that can transmit medical images with minimal distortion and high security. The proposed method selects two adjacent gray pixels whose least significant bit (LSB) is different from the relevant message bit and then calculates the distortion degree. We use the LSB pairing method to embed the secret matrix of patient record into… More >