Adaptive reversible video watermarking based on motion-compensated prediction error expansion with pixel selection

Vural, Cabir; Baraklı, Burhan

doi:10.1007/s11760-016-0881-x

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Author achieved the better robustness and channel capacity using the proposed approach. Vural et al [12] have identified the motion compensated frames based on the smoothness exist within continuous video frames. The block adaptive evaluation was also conducted to identify the pixel distortion and use it as the cover pixel for effective data hiding within videos.…”

Section: Related Workmentioning

confidence: 99%

Frame Selective and Dynamic Pattern Based Model for Effective and Secure Video Watermarking

Juneja¹,

Bansal²

2019

IJC

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Video watermarking enables the users to share the digital contents in public domain without any issue. However, video watermarking is also infected by various attacks that can even destroy the hidden watermark. The security, robustness and reliability are the key challenges of any Video watermarking technique. In this paper, such a robust and dynamic video watermarking framework is presented that can handle most of the existing issues. In this framework, the video is hiding on the selective frames and the preference of frames is done based on structural feature evaluation. After performing the frame selection, the featured analysis is accomplished on each frame to identify the effective cover blocks. The structure feature analysis based rules are applied to identify the most secure region over the frame. In the final stage, the histogram shift method is applied to perform data hiding. To improve the security, instead of hiding the complete image, the ECC (Elliptic Curve Cryptography) encrypted image is watermarked within the video frames. The analysis is performed on real time videos. The analysis results are generated in terms of MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio), SSIM (Structural Similarity Measure) and BCR (Bit Correct Ratio) parameters. The results identified that the proposed model has improved the effectiveness, robustness and security against various attacks. The comparative results are also validated against the DCT and DCT-SVD based video watermarking methods.

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Section: Related Workmentioning

confidence: 99%

Frame Selective and Dynamic Pattern Based Model for Effective and Secure Video Watermarking

Juneja¹,

Bansal²

2019

IJC

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“…Performance comparison of the proposed technique with [6,7,32,33] has been given in Table VIII. The comparison has been made with respect to several features like imperceptibility, watermark capacity, reversibility and ratio of extra side information with the pure watermark.…”

Section: Watermark Extractionmentioning

confidence: 99%

“…They are using motion vectors for watermark embedding but they are not targeting the ultrasound videos and have not mentioned anything for the reversibility of the original content. In this paper, the proposed approach is compared with the previous approaches [6,7,32,33], where the authors are using normal/medical videos for embedding the watermarks /reversible-watermark(s). The experimental comparison shows that the proposed approach validates the usefulness of the reversible watermarking in motion vectors for the protection of an ultrasound image sequence.…”

Section: Watermark Extractionmentioning

confidence: 99%

Protection of Ultrasound Image Sequence: Employing Motion Vector Reversible Watermarking

Habib¹,

Alfayez²

2019

IJACSA

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In healthcare information systems, medical data is very important for diagnosis. Most of the health institutions store their patients' data on third-party servers. Therefore, its security is very important, since the advent of advanced multimedia and communication technology, whereby digital contents are manipulated, copied, and duplicated without leaving any trace. In this paper, a reversible watermarking technique is applied to the patients' data (ultrasound image sequence). Since the traditional watermarking schemes can experience some permanent distortions that are not acceptable in the medical application. Thus, a reversible watermarking technique has been used, which can not only secure the ultrasound image sequence but also restore the original sequence back. For watermark embedding, the magnitude and phase angles of motion vectors of the image sequence are used that are obtained by using Full-Search block-based motion estimation algorithm. Before applying the motion estimation algorithm and watermark embedding, the histogram pre-processing is performed to avoid underflow/overflow. Unlike other state-of-the-art watermarking schemes that are reported in the last decades, the experimental results show that the proposed algorithm is simple, provides a much larger embedding capacity and better quality of the watermarked image sequence.

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“…Compared to the image case, there exist limited studies for reversible video watermarking. Prediction error between consecutive frames is utilized in [7] and [8] while interpolation error is used in [9]. A new data hiding method called recursive histogram modification is applied on video sequences in [10].…”

Section: Introductionmentioning

confidence: 99%

Multilevel Reversible Video Watermarking with Improvement on Occluded Areas

Yildirim¹

2018

Sakarya University Journal of Science

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In this paper, affect of occlusion for reversible video watermarking algorithms is focused in a multilevel concept. Motion compensated prediction error become higher between video frames which include occlusion areas. Thus, watermarking algorithm which exploits prediction error has small embedding capacity and poor image quality. In order to get maximum efficiency in a motion compensated video watermarking, occlusion detection algorithms should be taken into consider. In this study, a multilevel reversible video watermarking algorithm exploits histogram modification and occlusion detection algorithms has been proposed. Our method has better visual quality and embedding capacity.

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Adaptive reversible video watermarking based on motion-compensated prediction error expansion with pixel selection

Cited by 4 publications

References 9 publications

Frame Selective and Dynamic Pattern Based Model for Effective and Secure Video Watermarking

Frame Selective and Dynamic Pattern Based Model for Effective and Secure Video Watermarking

Protection of Ultrasound Image Sequence: Employing Motion Vector Reversible Watermarking

Multilevel Reversible Video Watermarking with Improvement on Occluded Areas

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