Analysis of Watermarking Techniques

Malik, Gunjan; Kumar, Tarun

doi:10.5120/ijca2016908976

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…It only imparts frequency information without location updates [12]. It is full video/image transform, implying that any changes made to transform coefficients will affect the entire video/image [6]. This technique gives robust results against geometric attacks like cropping, scaling, and translation.…”

Section: Transforms Used In Watermarking Scheme 31 Dftmentioning

confidence: 99%

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Wavelet Analysis in Video Watermarking through Wavelet Transform Scheme

Malik¹,

Kumar²,

Agarwal³

2017

IJCA

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Intellectual and copyright protection is one of the major issues faced by copyright owners. Easy access to Internet and all the digital media such as audios, images, digital documents and videos, poses great threat to copyright owners as their work gets manipulated, forged, redistributed conveniently through illegal means. As an effective solution to this problem, concept of Digital Watermarking has been used. Watermarks can be of the form images, text, binary logos, signatures, and numbers. They are used for storing information about the copyright owner, source of data, and authentic users. In the proposed work, video watermarking technique has been shown highlighting comparative analysis of db wavelets based on different quality parameters. Each of the db wavelets is applied on the randomly selected frames from the input coloured video using random number that works as a key for the proposed extraction algorithm. It is shown that not all db wavelets support watermarking scheme. Out of 45 wavelets, 12 db wavelets were applicable for watermarking. The original watermark image and the extracted watermark image are then used as the basis against various quality parameters to check if the imperceptibility of the watermark is retained after watermark extraction. The proposed watermarking scheme is imperceptible against various quality parameters such as Peak-signal-to-noise ratio, Mean-square error, maximum difference, and normalized absolute error.

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Section: Transforms Used In Watermarking Scheme 31 Dftmentioning

confidence: 99%

“…It can withstand attacks like sharpening, blurring, filtering but unlike DWT it lack in imperceptibility as it cannot be modelled as HVS. Applying mid-band frequency can provide better trade-off between imperceptibility and robustness [6]. Real time applications of DCT are pan card, employee e-card, or fingerprint identity.…”

Section: Dctmentioning

confidence: 99%

Wavelet Analysis in Video Watermarking through Wavelet Transform Scheme

Malik¹,

Kumar²,

Agarwal³

2017

IJCA

Self Cite

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Ownership Protection on Digital Elevation Model (DEM) Using Transform-Based Watermarking

Amhar

Giri

Silalahi³

et al. 2022

IJGI

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This research aims to protect Digital Elevation Model (DEM) data from piracy or counterfeiting. An invisible watermark inserted into the data, which will not considerably change the data value, is necessary. The proposed method involves the use of the two-dimensional discrete cosine transform (2D DCT), a combination of 2D DCT and discrete wavelet transform (DWT), and two-dimensional discrete Fourier transform (2D DFT) in the frequency domain. The data used include a National DEM file downloaded from the geoportal of the Geospatial Information Agency (Badan Informasi Geospasial—BIG). Three files represent mountainous, lowland/urban, and coastal areas. An “attack” is also conducted on the watermarked DEM by cropping. The results indicate that the watermarked DEM is well recognized. The watermark can be read 100% for 2D DCT, while that for 2D DFT can be read 90.50%. The distortion value of the elevation data under the DCT technique demonstrates the smallest maximum value of 0.1 m compared with 4.5 and 1.1 m for 2D DFT and 2D DCT–DWT. Meanwhile, the height difference (Max Delta), the peak signal-to-noise ratio, and the root mean squared error (RMSE) are highest in mountainous, lowland, and coastal areas, respectively. Overall, the 2D DCT is also superior to the 2D DFT and the2D DCT–DWT. Although only one can recognize the nine watermarks inserted on each sheet, DEMs attacked by the cropping process can still be identified. However, this finding can sufficiently confirm that DEMs belong to BIG.

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Analysis of Watermarking Techniques

Cited by 2 publications

References 8 publications

Wavelet Analysis in Video Watermarking through Wavelet Transform Scheme

Wavelet Analysis in Video Watermarking through Wavelet Transform Scheme

Ownership Protection on Digital Elevation Model (DEM) Using Transform-Based Watermarking

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