A new robust semi-blind digital image watermarking approach based on LWT-SVD and fractal images

Ghaderi, Kayvan; Akhlaghian, Fardin; Moradi, Parham

doi:10.1109/iraniancee.2013.6599633

Cited by 12 publications

(4 citation statements)

References 8 publications

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“…Entropy values have been used to determine watermark embedding in this method, according to the images' entropy. Researchers Ghaderi et al [14] developed a method that utilized LWT and SVD. An author performs a 4-level LWT on the HL and LH sub bands before applying the SVD to the HL and LH sub bands.…”

Section: Related Workmentioning

confidence: 99%

Robust Watermarking Scheme for NIfTI Medical Images

Kumar¹,

Singh²,

Kumar³

et al. 2022

Computers, Materials &Amp; Continua

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Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI) technologies are widely used in medical field. Within the last few months, due to the increased use of CT scans, millions of patients have had their CT scans done. So, as a result, images showing the Corona Virus for diagnostic purposes were digitally transmitted over the internet. The major problem for the world health care system is a multitude of attacks that affect copyright protection and other ethical issues as images are transmitted over the internet. As a result, it is important to apply a robust and secure watermarking technique to these images. Notably, watermarking schemes have been developed for various image formats, including .jpg, .bmp, and .png, but their impact on NIfTI (Neuroimaging Informatics Technology Initiative) images is not noteworthy. A watermarking scheme based on the Lifting Wavelet Transform (LWT) and QR factorization is presented in this paper. When LWT and QR are combined, the NIfTI image maintains its inherent sensitivity and mitigates the watermarking scheme's robustness. Multiple watermarks are added to the host image in this approach. Measuring the performance of the graphics card is done by using PSNR, SSIM, Q (a formula which measures image quality), SNR, and Normalized correlation. The watermarking scheme withstands a variety of noise attacks and conversions, including image compression and decompression.

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Section: Related Workmentioning

confidence: 99%

Robust Watermarking Scheme for NIfTI Medical Images

Kumar¹,

Singh²,

Kumar³

et al. 2022

Computers, Materials &Amp; Continua

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“…The powers of structural, directional, and functional control are the most essential issues in nanoscience and emerging nanotechnology. Many attempts have been made to regulate the spatial distribution of nanoparticles (NPs) as well as their physical and functional features [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Fractal Dimension Image Processing for Feature Extraction and Morphological Analysis: Gd3+/13X/DOX/FA MRI Nanocomposite

Ghaderi

2023

Journal of Nanomaterials

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One of the most fundamental subjects in nanoscience and nanotechnology is structural analysis. We employed a scanning electron microscope (SEM) image of the manufactured Gd3+/13X/DOX/FA nanocomposite in this study. The size, dimensions, and morphology of nanocomposite materials were studied to ensure the uniformity and homogeneity of SEM images. This is the first study to look at segmented SEM images for fractal dimension (FD) and other statistical criteria, including average, maximum, minimum, skewness, and range for magnetic resonance imaging (MRI) nanocomposite. The average of FD (FDavg), the standard deviation of FD (FDsd), and the lacunarity of FD (FDlac) fractal data analysis criteria were also employed. The findings show that particle sizes and shapes vary because the minimum-to-maximum range is not zero, and our data provide a reasonable range. This interpretation is further supported by an analysis of the nanocomposite’s SEM image. At first glance, the image seemed to be uniform. However, when the calculations were performed, it was discovered that the generated particles were not particularly uniform. The particles were uniformly dispersed throughout all surfaces, although their sizes, dimensions, and morphologies varied. In conclusion, the study was supported by fractal data analysis, emphasizing the importance of structural analysis for future research, particularly for medical applications like MRI.

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“…Ghaderi et.al. [9] proposed a novel semi-blind watermarking scheme for image copyright protection, which is developed in the Lifting Wavelet Transform (LWT) and is based on Singular Value Decomposition (SVD). They have used fractal codification for representing the compactness of watermark image.…”

Section: Introductionmentioning

confidence: 99%

Blind digital watermarking algorithm based on DCT domain and fractal images

Arun

Kabi

Saha

et al. 2014

2014 Conference on IT in Business, Industry and Government (CSIBIG)

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Multimedia distribution across public network and internet is growing fast. With diverse evolution in technology of distribution and storage, various factors are challenging multimedia and internet technologies. Digital watermarking solves the problems of several threats and protects the digital data from being compromised or altered. It also provides copyright protection to avoid illegal modification of digital data. In this paper we have proposed a blind digital watermarking algorithm based on fractal images on Discrete Cosine Transform (DCT) domain. The fractal code is converted to its respected binary images and used as a watermark image. The cover image is decomposed to its respective grayscale equivalents of RGB components. The fractal codes as watermark binary images are embedded into grayscale equivalent of RGB components of cover image. The embedding is done in mid frequency to secure the codes from several attacks. The robustness and imperceptibility of the algorithm is shown in results and analysis.

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A new robust semi-blind digital image watermarking approach based on LWT-SVD and fractal images

Cited by 12 publications

References 8 publications

Robust Watermarking Scheme for NIfTI Medical Images

Robust Watermarking Scheme for NIfTI Medical Images

Fractal Dimension Image Processing for Feature Extraction and Morphological Analysis: Gd3+/13X/DOX/FA MRI Nanocomposite

Blind digital watermarking algorithm based on DCT domain and fractal images

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