Reversible video data hiding using neighbouring similarity

Yeh, Hsiu-Lien; Gue, Shu-Tsai; Tsai, Pei-Hsun; Shih, Wei-Kuan

doi:10.1049/iet-spr.2012.0233

Cited by 17 publications

(20 citation statements)

References 13 publications

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“…This technique has high embedding capacity relative to other techniques [3]. Yeh et al [4] proposed data hiding in videos based on neighboring similarity by calculating prediction errors. Then histogram shifting scheme was applied to these errors to develop the reversible data hiding scheme.…”

Section: Related Workmentioning

confidence: 98%

Data hiding in videos using Background Subtraction

Singh

2015

2015 2nd International Conference on Recent Advances in Engineering &Amp; Computational Sciences (RAECS)

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Nowadays, Video Steganography has emerged as the popular cover medium for hiding of information because of its storage capacity. The selection of pixels for hiding data is very crucial and should be random for security measures. Therefore, we have explored the natural randomness by using such video sequences which contain dynamic variations as a cover. The embedding is done by measuring motion in the frames. It has been achieved by using background subtraction technique which estimates the background to detect foreground pixels. These foreground pixels are then used for hiding data. The proposed algorithm is tested on public available Star dataset for validation. Experimental results show that the proposed algorithm can be used for hiding data as it provides good storage capacity and video quality.

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Section: Related Workmentioning

confidence: 98%

Data hiding in videos using Background Subtraction

Singh

2015

2015 2nd International Conference on Recent Advances in Engineering &Amp; Computational Sciences (RAECS)

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“…In 2014, H. Yeh et.al, [20] proposed the watermarking algorithm for videos using the neighbouring similarity. Prediction encoding has been employed to compute the prediction errors and then all of the prediction errors are explored to develop a histogram-based reversible video watermarking algorithm.…”

Section: Literature Reviewmentioning

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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“…In another study, Yeh et al [17] developed the neighboring similarity (NS) method. They take advantage of the similarity of two adjacent frames in a video to create a prediction error.…”

Section: Introductionmentioning

confidence: 99%

“…The selection is made by calculating the ratio between the peak point frequency and the number of shifted values. Overall, that research is to refine that in [17], even though it still has some spaces for improvement, considering the number of changed pixels during the shifting process.…”

Section: Introductionmentioning

confidence: 99%

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Video-based Data Hiding by Exploring Prediction Error and Histogram Shifting

2022

IJIES

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Information has been crucial in supporting daily activities. Many tasks must be accomplished by transferring not only public but also private information. This situation has brought the necessity for protecting it during transmission. Some mechanisms introduced, like data hiding, are still challenging, considering the quality of the data and the secret size can be protected. This research presents a reversible data hiding method for digital video based on prediction error and histogram shifting to approach those problems. There are six kinds of prediction errors used, three are created from two adjacent frames, and three are from a single frame. The selection of the shift location is determined by the histogram location, which has the highest peak point. The histogram is obtained by calculating the frequency of the subtraction of each value from its predicted value. The PSNR calculated from the stego and the original videos has an average of 73.45 dB. This value demonstrates that the proposed method outperforms the previous research.

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Reversible video data hiding using neighbouring similarity

Cited by 17 publications

References 13 publications

Data hiding in videos using Background Subtraction

Data hiding in videos using Background Subtraction

Protection of Ultrasound Image Sequence: Employing Motion Vector Reversible Watermarking

Video-based Data Hiding by Exploring Prediction Error and Histogram Shifting

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