Spread-spectrum watermarking of audio signals

Kirovski, Darko; Malvar, H.S.

doi:10.1109/tsp.2003.809384

Cited by 328 publications

(166 citation statements)

References 13 publications

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“…Darko Kirovski and Henrique S. Malvar [13] proposed present several novel mechanisms for effective encoding and detection of direct-sequence spread-spectrum watermarks in audio signals. The developed techniques aim at 1) Improving detection convergence and robustness 2) Improving watermark imperceptiveness, 3) Preventing desynchronization attacks, 4) Alleviating estimation/removal attacks, and finally, 5) Establishing covert communication over a public audio channel.…”

Section: Historymentioning

confidence: 99%

Advanced LBP Fragile Watermarking System for Image Tamper Detection and Recovery

2017

IJMTER

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Abstract-This paper describes as digital images are used in a wide range of applications and for multiple purposes. They also play an important role in the storage and transfer of visual information, especially the confidential ones. With this widespread usage of digital images, in addition to the increasing number of tools and software of digital images editing, it has become easy to manipulate and change the actual information of the image. Therefore, it has become necessary to check the authenticity and the integrity of the image by using modern and digital techniques, which contribute to analysis and understanding of the image content and then make sure of their integrity. Digital image fragile watermarking is an information hiding technique which adds the watermark into the host image for authentication .while achieving the high integrity one should not compromise with quality distortion of images. numbers of watermarking schemes exist today for balancing between the tamper detection rate and quality of reconstructed images in propose scheme we aim at maintain high tamper detection rate as well as high Peak to Signal Noise Ratio (PSNR) of reconstructed images for their quality. For that we utilize Local Binary Pattern (LBP) for this purpose to obtain the optimal solution. In this paper we used a fragile image watermarking scheme with recover ability based on local binary pattern (LBP). The local binary pattern operator used to extract localized spatial features. A local binary pattern is used to represent the localized relations of a pixel with its neighborhood pixels. Every pixel measured by the LBP operator and obtained its own local binary pattern as representation of local spatial relations. We utilizes the LBP operator to generate authentication data which are embedded into each image block with 3×3 pixels size for tamper detection and recovery. The recovery information is obtained by calculating the mean value of each image block, and then the mean value is converted into a binary string which is embedded into eight neighboring pixels LSBs of each image block for image recovering. In the paper consider input as 256×256 as well as 512×512 dimension image, one of the advantage compare to other existing system is that it can also processed the color image. The quality is calculated by the PSNR but in the proposed scheme PSNR at peak point is also calculated to achieve better result. General Terms--Digital image watermarking, fragile image watermarking, local binary pattern (LBP), PSNR (peak signal to noise ratio)

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Section: Historymentioning

confidence: 99%

Advanced LBP Fragile Watermarking System for Image Tamper Detection and Recovery

2017

IJMTER

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“…As for our scheme, the payload, with 4 bits per frame, is $ 187 bps. This is a comparatively high capacity when compared to audio watermarking schemes described in [15,[41][42][43][44][45][46][47][48][49]51]. The payload capacity of the scheme can be improved by embedding more than 4 bits in each frame by modifying more elements in the second column of U.…”

Section: Capacitymentioning

confidence: 99%

“…Most audio watermarking algorithms use either a time domain [6,7] or frequency domain [8][9][10] masking property to embed a watermark [3,4]. Our previous work has considered a watermarking scheme utilizing the CSPE algorithm to encode the cover signal [60].…”

Section: Introductionmentioning

confidence: 99%

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

2011

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a b s t r a c tThis paper presents a blind audio watermarking algorithm based on the reduced singular value decomposition (RSVD). A new observation on one of the resulting unitary matrices is uncovered. The proposed scheme manipulates coefficients based on this observation in order to embed watermark bits. To preserve audio fidelity a thresholdbased distortion control technique is applied and this is further supplemented by distortion suppression utilizing psychoacoustic principles. Test results on real music signals show that this watermarking scheme is in the range of imperceptibility for human hearing, is accurate and also robust against MP3 compression at various bit rates as well as other selected attacks. The data payload is comparatively high compared to existing audio watermarking schemes.

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“…Van der Veen et al published an audio watermarking technology that survives air transmission on an acoustical path and numerous other robustness tests while being perceptionally transparent [2]. The algorithm of Kirovski and Malvar [3] embeds about 1 bit per second (half as much as the one in [1]) and is even more robust (against the Stirmark Benchmark [4]). Arnold et al presented an adaptive spread phase modulation (ASPM) that embeds an inaudible watermark with good robustness [5].…”

Section: Introductionmentioning

confidence: 99%

Pit Stop for an Audio Steganography Algorithm

Westfeld

Wurzer

Fabián

et al. 2013

Communications and Multimedia Security

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Abstract. Steganography plays an important role in the field of secret communication. The security of such communication lies in the impossibility of proving that secret communication is taking place.We evaluate the implementation of a previously published spread spectrum technique for steganography in auditive media. We have unveiled and solved several weaknesses that compromise undetectability.The spread-spectrum approach of the technique under evaluation is rather unusual for steganography and makes the secret message fit to survive A/D and D/A conversions of analogue audio telephony, re-encoded speech channels of GSM/UMTS, or VoIP. Its impact to signal statistics, which is at least concealed by the lossy channel, is reduced. There is little published on robust audio steganography, its steganalysis, and evaluation, with the possible exception of audio watermarking, where undetectability is not as important.

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Spread-spectrum watermarking of audio signals

Cited by 328 publications

References 13 publications

Advanced LBP Fragile Watermarking System for Image Tamper Detection and Recovery

Advanced LBP Fragile Watermarking System for Image Tamper Detection and Recovery

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

Pit Stop for an Audio Steganography Algorithm

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