A secure and robust image watermarking system using wavelet domain

Siddiqui, Amra; Kaur, Arashdeep

doi:10.1109/confluence.2017.7943222

Cited by 9 publications

(7 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, our proposed method implements the blind extraction approach. We also compared the results of our proposed method with those reported by [7,13,18,23] shown in Table 4. The normalized correlation were calculated between the watermark image and recovered image.…”

Section: Experimental Results Of Svd and Dwtmentioning

confidence: 99%

“…In addition, the authors employed a median filter function to smooth the image before decomposition took place. Siddiqui et al proposed a hybrid DWT and SVD watermarking approach, in which the host image was decomposed into four bands: LL, LH, HL, and HH [7]. Then the LL subband was further decomposed into the fourth level.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In most cases, LL (i.e. CA) and HL are decomposed [7,10]. So, we also started our decomposition with the LL band, and we further decomposed the other DWT frequency band i.e.…”

Section: Decomposition Schemementioning

confidence: 99%

“…Although research into the means to protect the security of biometric data is ongoing, the efforts of those intending to violate the security of these data also continue, with the intent of attacking or bypassing any algorithms designed to ensure data security [5]. The aim of research in the field of watermarking and steganography is to achieve these qualities, which are imperceptibility and robustness [6,7]. A watermarking approach can be implemented in two ways, a spatial domain and a frequency domain approach.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Analysis of biometric data using watermarking techniques

2020

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

This paper evaluates and analyses the discrete wavelet transform (DWT) frequency bands for embedding and extracting of the biometric data using DWT single level and multilevel watermarking approach with and without the use of alpha blending approach. In addition, singular value decomposition (SVD) combined with DWT is used to embed and extract the watermark image. The performance of compression and decompression approaches has been analyzed to examine the robustness and to check whether the compression function does destroy the integrity of the watermarked image. We investigate the proposed approach to understand how robust the watermarked on different sub-band is against the image processing and geometric attacks. The experimental results show that the DWT multilevel and SVD watermarking approach is more robust than the other watermarking methods implemented in this paper. The DWT bands dominate the approximate coefficient band (LL) in high-intensity alpha value. When the intensity is reduced, the coefficient standout to be very robust against the remaining bands.

show abstract

Section: Experimental Results Of Svd and Dwtmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

“…In most cases, LL (i.e. CA) and HL are decomposed [7,10]. So, we also started our decomposition with the LL band, and we further decomposed the other DWT frequency band i.e.…”

Section: Decomposition Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of biometric data using watermarking techniques

2020

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

show abstract

“…▪ For example, if a block index shown below is input, let X = 30, y = 33, N = 7, and n = 2 S1 = [8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37] S2 = [9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,36,34,32,30,28,26,24,22,20,18,16,14,12,…”

Section: Graph Theory and Random Selectionmentioning

confidence: 99%

A High Capacity Embedding Scheme Based on Graph Theory Randomness and Bit Difference for Covert Communication

Abbas¹,

Thahab²

2019

ijeei

View full text Add to dashboard Cite

Stenographic techniques are hiding methods that are used in secret communications to transmit secret data inside a carrier media. In this paper, a new image steganography technique based on graph theory and bit difference is proposed. Secret image is divided into blocks and randomized based on graph theory. The cover image is divided into four blocks and each secret image pixel is grouped into four two-bit groups and concealed inside the cover media. The embedding algorithm is based on a modified version of bit difference which is considered more secure. The proposed method is applied in the spatial and transform domain using Integer wavelet transform (IWT) since, IWT is less distortional in retrieving images compared to the discrete wavelet transform (DWT). Performance analysis of the proposed scheme is tested using peak signal to noise ratio (PSNR) and embedding capacity using various cover image formats such as (TIFF, PNG, BMP, and JPEG). Results show that the proposed scheme is superior over several embedding schemes in terms of capacity and visual symmetry.

show abstract