An intelligent reversible watermarking system for authenticating medical images using Wavelet and PSO

Balasamy, K.; Ramakrishnan, S.

doi:10.1007/s10586-018-1991-8

Cited by 46 publications

(30 citation statements)

References 22 publications

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“…For the invisibility capability, the structural similarity image index (SSIM) is an image quality assessment parameter that is also used to check the resemblance between both the color cover image (CI) and the watermarked color image (MI) [11]. Besides, SSIM aims to enhance conventional schemes such as PSNR, and it turns out to be inconsistent with the human visual system (HVS) [33]…”

Section: B Performance Parametersmentioning

confidence: 99%

A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

2020

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Image watermarking is a robust solution for solving key issues like copyright protection and proof of ownership of digital data. Existing schemes of image watermarking mostly used grayscale or binary images as embedded watermarks, while only a few watermarking schemes are developed for color images. In this paper, we propose a novel robust semi-blind image watermarking scheme based on finite ridgelet transform (FRT), discrete wavelet transform (DWT), singular value decomposition (SVD), particle swarm optimization (PSO), and Arnold transform to protect copyright and verify the authenticity of color images. Firstly, the color image is converted from RGB to YCbCr color space, and the luminance component (Y) is taken into account to insert the watermark data. In this study, the principal component (PC) of the watermark image is directly inserted into the corresponding singular value of the cover image by the scaling factor to avoid the false positive problem (FPP). To further improve security, Arnold transform is applied to process the Y channel of the watermark image before inserting it in the cover image. Besides, PSO optimizes the embedding factor matrices. The qualitative evaluation factors like peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are used to assess the visual quality, while normalized correlation coefficient (NCC) is used to assess the resemblance between the watermarked and the restored watermarked images. The performance of the proposed scheme is evaluated using geometric, non-geometric, and combinational attacks, and its comparison is performed with different image watermarking schemes to prove its robustness.

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Section: B Performance Parametersmentioning

confidence: 99%

A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

2020

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“…The major limitations of this approach are the need for embedding the feature-bit matrix and only the ROI part of the image can be retrieved at extraction. A novel medical image authentication approach was proposed by Balasamy and Ramakrishnan [9] using Discrete Wavelet Transform (DWT) and Particle Swarm Optimization (PSO). This approach finds optimal wavelet coefficients for concealing the watermark data using PSO to produce a watermarked image with low distortion.…”

Section: Related Workmentioning

confidence: 99%

“…Additional data is required for the extraction process. Transform based watermarking methods are proposed [9,41,42], and can recover the complete original image after extracting the watermark. However, image distortion is high in comparison to low embedding capacity.…”

Section: Comparison With Existing Approachesmentioning

confidence: 99%

ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

Qasim

Aspin

Meziane

et al. 2018

Multimed Tools Appl

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Reversible and imperceptible watermarking is recognized as a robust approach to confirm the integrity and authenticity of medical images and to verify that alterations can be detected and tracked back. In this paper, a novel blind reversible watermarking approach is presented to detect intentional and unintentional changes within brain Magnetic Resonance (MR) images. The scheme segments images into two parts; the Region of Interest (ROI) and the Region of Non Interest (RONI). Watermark data is encoded into the ROI using reversible watermarking based on the Difference Expansion (DE) technique. Experimental results show that the proposed method, whilst fully reversible, can also realize a watermarked image with low degradation for reasonable and controllable embedding capacity. This is fulfilled by concealing the data into 'smooth' regions inside the ROI and through the elimination of the large location map required for extracting the watermark and retrieving the original image. Our scheme delivers highly imperceptible watermarked images, at 92.18-99.94 dB Peak Signal to Noise Ratio (PSNR) evaluated through implementing a clinical trial based on relative Visual Grading Analysis (relative VGA). This trial defines the level of modification that can be applied to medical images without perceptual distortion. This compares favorably to outcomes reported under current state-of-art techniques. Integrity and authenticity of medical images are also ensured through detecting subsequent changes enacted on the watermarked images. This enhanced security measure, therefore, enables the detection of image manipulations, by an imperceptible approach, that may establish increased trust in the digital medical workflow.

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“…These interfaces provide access to patient records containing text and image data [ 1 ]. This sharing of this data, and in particular images on the Internet, exposes them to unauthorized manipulation [ 2 ], despite existing security tools such as access control. Watermarking has therefore been proposed to increase the sharing security by allowing keeping the patients’ data confidential and verifying the medical images' integrity [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

A robust blind medical image watermarking approach for telemedicine applications

et al. 2021

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In order to enhance the security of exchanged medical images in telemedicine, we propose in this paper a blind and robust approach for medical image protection. This approach consists in embedding patient information and image acquisition data in the image. This imperceptible integration must generate the least possible distortion. The watermarked image must present the same clinical reading as the original image. The proposed approach is applied in the frequency domain. For this purpose, four transforms were used: discrete wavelets transform, non-subsampled contourlet transform, non-subsampled shearlet transform and discreet cosine transform. All these transforms was combined with Schur decomposition and the watermark bits were integrated in the upper triangular matrix. To obtain a satisfactory compromise between robustness and imperceptibility, the integration was performed in the medium frequencies of the image. Imperceptibility and robustness experimental results shows that the proposed methods maintain a high quality of watermarked images and are remarkably robust against several conventional attacks. Keywords Medical image Á Digital watermarking Á Discrete wavelet transform Á Non-subsampled contourlet transform Á Non-subsampled shearlet transform Á Discreet cosine transform Á Schur decomposition

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An intelligent reversible watermarking system for authenticating medical images using Wavelet and PSO

Cited by 46 publications

References 22 publications

A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images

A robust blind medical image watermarking approach for telemedicine applications

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