DCT-based watermark recovering without resorting to the uncorrupted original image

Piva, Alessandro; Barni, Mauro; Bartolini, Franco; Cappellini, V.

doi:10.1109/icip.1997.647964

Cited by 281 publications

(122 citation statements)

References 7 publications

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“…[12], a generic quantization index modulation (QIM) data hiding method [13] (with a quantization step size of 5, an embedding rate of 0.1bits per pixel (bpp)), and generic LSB. For all the data hiding methods, different random signals are embedded into different images.…”

Section: Resultsmentioning

confidence: 99%

Steganalysis based on Markov Model of Thresholded Prediction-Error Image

Zou

Shi

et al. 2006

2006 IEEE International Conference on Multimedia and Expo

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A steganalysis system based on 2-D Markov chain of thresholded prediction-error image is proposed in this paper. Image pixels are predicted with their neighboring pixels, and the prediction-error image is generated by subtracting the prediction value from the pixel value and then thresholded with a predefined threshold. The empirical transition matrixes of Markov chain along the horizontal, vertical and diagonal directions serve as features for steganalysis. Support vector machines (SVM) are utilized as classifier. The effectiveness of the proposed system has been demonstrated by extensive experimental investigation. The detection rate for Cox et al.'s non-blind spread spectrum (SS) data hiding method, Piva et al.'s blind SS method, and a generic QIM method (as embedding data rate being 0.1 bpp (bits per pixel)) are all above 90% over an image database consisting of approximately 4000 images. For generic LSB method (with various embedding data rates), our steganalysis system achieves a detection rate above 85% as the embedding data rate is 0.1 bpp and above.

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Section: Resultsmentioning

confidence: 99%

Steganalysis based on Markov Model of Thresholded Prediction-Error Image

Zou

Shi

et al. 2006

2006 IEEE International Conference on Multimedia and Expo

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“…The embedded watermarks may be either visible [16,22] or invisible (audible or inaudible in case of audio) [6,8,9,32,28]. They cannot be removed or detected by anyone other than the creator.…”

Section: Copyright-violation Detection and Subscriber's Concernsmentioning

confidence: 99%

A digital rights management scheme for broadcast video

Emmanuel

Kankanhalli

2003

Multimedia Systems

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Abstract. Many watermarking techniques have been proposed for digital video and digital broadcast video. In general, they address the seller's or broadcaster's concerns, such as copyright-violation deterrence, copyright-violation detection and copy protection. Some of them provide for data integrity (tamper proofing), which is a shared concern of both subscriber and broadcaster. In all these cases, the watermark generation and embedding is performed or controlled by the seller or broadcaster. Therefore, a broadcaster with malicious intentions could, with manipulation, falsely implicate an innocent subscriber in copyright violation. This could be a major concern for subscribers.In this paper, we propose an integrated solution to manage the broadcaster's copyright and subscriber's false-implication concern (subscriber's rights) for digital video broadcasts. The proposed novel approach makes use of interactive watermarking techniques and protocols to help protect digital rights of all parties involved in video broadcasting.

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“…One possibility to obtain these fixed embedding positions has been proposed by Piva et al [11] and works as follows: Embed WM along a zig-zag scan of the AC coefficients similar to the walk in the JPEG compression algorithm (but on the entire N × N DCT-transformed image). Embedding of the watermark begins at a predetermined diagonal l, which becomes part of the common input.…”

Section: Solutionmentioning

confidence: 99%

Non-interactive Watermark Detection for a Correlation-Based Watermarking Scheme

Adelsbach

Sadeghi

2005

Communications and Multimedia Security

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Abstract. Cryptographic techniques have been deployed to securely prove the presence of a watermark in stego-data without disclosing any security critical information to the detecting party.This paper presents a detailed practical construction and implementation results of a correlation-based non-blind watermarking scheme in the non-interactive zero-knowledge setting. We extensively describe the modifications and hurdles that had to be overcome to transform a wellknown watermarking scheme -whose general detection principle is applied in many other known schemes -into a two-party setting where the critical detection input, i.e. the watermark vector and the original data is cryptographically concealed from the verifying party using a commitment scheme. Our prototype implementation is very efficient and is an evidence of the practical feasibility of zero-knowledge watermark detection.

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DCT-based watermark recovering without resorting to the uncorrupted original image

Cited by 281 publications

References 7 publications

Steganalysis based on Markov Model of Thresholded Prediction-Error Image

Steganalysis based on Markov Model of Thresholded Prediction-Error Image

A digital rights management scheme for broadcast video

Non-interactive Watermark Detection for a Correlation-Based Watermarking Scheme

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