Reversible data hiding based on histogram shifting of prediction errors using two predictors

Jaara, Enas N.; Jafar, Iyad F.

doi:10.1109/aeect.2015.7360540

Cited by 5 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The intensity wraps around and low hiding capacity of salt/pepper artefacts, for example, may now be remedied, among other common issues [14]. [5]. Another study on this subject was provided(Kuo etal in 2008) using Block Segmentation technique is the small modification scheme used by Ni et al (2006) in order to adjust the mechanism used to save data and increase the capacity for data hiding [6,7].…”

Section: Fig 1 Pixel-based Techniques Used For Reversible Data Hiding...mentioning

confidence: 99%

Contemporary Approaches On Reversible Data Hiding In Iris Image Using Deep Learning Techniques

2024

Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security,

View full text Add to dashboard Cite

The concept of reversible data concealing is crucial for secret communication. After the extraction stages, the protected information can be completely rebuilt in addition to the hidden data being removed. Pixel, Block and Interpolation based algorithms have seen substantial development over the past decade, employing the spatial-frequency domain and other related techniques. The goal of this research work is to categorize and describe the various methods, inner groups and research papers related to the idea of Reversible Data Hiding (RDH). In order to protect privacy, this research suggests a revolutionary iris image data concealing strategy. Here, private information is incorporated into the iris image in a way that has the least negative effect on iris recognition. The Syndrome Trellis Coding (STC) architecture is applied, limiting changes to the embedded data and to the regions that infrequently affect iris identification. A new distortion function is also proposed to enumerate the impression of data implanting on recognition of Iris, which assigns high embedding cost to locations with strong iris features. According to experimental findings, enough information can be incorporated into the iris image while sustaining excellent identification accuracy by employing the proposed technique.

show abstract

Section: Fig 1 Pixel-based Techniques Used For Reversible Data Hiding...mentioning

confidence: 99%

Contemporary Approaches On Reversible Data Hiding In Iris Image Using Deep Learning Techniques

2024

Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security,

View full text Add to dashboard Cite

show abstract

“…This method increases the standard histogram translation process and reduces the number of columns and distortion. We can find a lot of research work that applied classical histogram translation [19,20] and difference expansion [21,22] to predict errors. Reversible watermarking systems based on lossless data compression attempt to compress some cover images to create capacity for embedding watermark bits.…”

Section: Related Workmentioning

confidence: 99%

Reversible Watermarking Method with Low Distortion for the Secure Transmission of Medical Images

Taj¹,

Feng²,

Khurram³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

In telemedicine, the realization of reversible watermarking through information security is an emerging research field. However, adding watermarks hinders the distribution of pixels in the cover image because it creates distortions (which lead to an increase in the detection probability). In this article, we introduce a reversible watermarking method that can transmit medical images with minimal distortion and high security. The proposed method selects two adjacent gray pixels whose least significant bit (LSB) is different from the relevant message bit and then calculates the distortion degree. We use the LSB pairing method to embed the secret matrix of patient record into the cover image and exchange pixel values. Experimental results show that the designed method is robust to different attacks and has a high PSNR (peak signal-to-noise ratio) value. The MRI image quality and imperceptibility are verified by embedding a secret matrix of up to 262,688 bits to achieve an average PSNR of 51.657 dB. In addition, the proposed algorithm is tested against the latest technology on standard images, and it is found that the average PSNR of our proposed reversible watermarking technology is higher (i.e., 51.71 dB). Numerical results show that the algorithm can be extended to normal images and medical images.

show abstract

“…An adjustable prediction-error expansion scheme that is free of the location map was proposed in [21]. In other algorithms, increasing the embedding capacity was approached by proposing algorithms that compute predictions based on multiple predictors [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

SARDH: A novel sharpening-aware reversible data hiding algorithm

Jafar

Darabkh

Saifan

2016

Journal of Visual Communication and Image Representation

Self Cite

View full text Add to dashboard Cite

Reversible data hiding based on histogram shifting of prediction errors using two predictors

Cited by 5 publications

References 15 publications

Contemporary Approaches On Reversible Data Hiding In Iris Image Using Deep Learning Techniques

Contemporary Approaches On Reversible Data Hiding In Iris Image Using Deep Learning Techniques

Reversible Watermarking Method with Low Distortion for the Secure Transmission of Medical Images

SARDH: A novel sharpening-aware reversible data hiding algorithm

Contact Info

Product

Resources

About