High capacity data hiding methods based on spline interpolation

Benhfid, Amine; Ameur, El Bachir; Taouil, Youssef

doi:10.1109/icmcs.2016.7905641

Cited by 9 publications

(6 citation statements)

References 17 publications

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“…To divide the histogram, we use Eqs. (11), (12), and (13), where is the PE value range, and is the number of the partition, is the divided partition. Fig.…”

Section: Data Embeddingmentioning

confidence: 99%

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Enhancing Quality of the Stego Image by Using Histogram Partition and Prediction Error

Islamy¹,

Ahmad²

2021

IJIES

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The widespread use of the internet to communicate with each other can introduces data security issues. Therefore, a reliable technique to secure information is becoming mandatory. Data hiding is a method to secure data by hiding it in cover media. In this research, we present a secure data hiding method by using images as cover. This research proposed the use of prediction error (PE) of images and utilization of the histogram-based method to conceal data. The histogram-based method can conceal data and still preserve the quality of the image. However, its lower hiding space can be a drawback. To overcome this, instead of using a histogram from the image's pixel, we calculate the error value of images and create a histogram from it. After that, we divide the histogram into partitions, whose peak is as the reference point for the embedding process. We utilize more than one error value in each partition to further increase the embedding space. Based on the experimental result, with the same image dataset, the average of PSNR values improved by 17.94 dB for general images and 14.95 dB for medical images compared to previous methods. These increases are statistically significant for the visual image quality, where the final PSNR values are between 61 and 66 dB, and between 62 and 68 dB for general and medical images, respectively. It is higher than the minimum standard of stego image quality, which is 30 dB.

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“…To divide the histogram, we use Eqs. (11), (12), and (13), where is the PE value range, and is the number of the partition, is the divided partition. Fig.…”

Section: Data Embeddingmentioning

confidence: 99%

“…It uses differences between the original pixel and the error value of the original pixel. Next, there are other reliable schemes, such as interpolation [10][11][12]. The main goal of the interpolation scheme is to utilize the enlargement of the image resolution.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Quality of the Stego Image by Using Histogram Partition and Prediction Error

Islamy¹,

Ahmad²

2021

IJIES

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“…Spatial domain and transform domain are the main approaches in steganography. Least Significant Bit technique (LSB) is the most famous technique in the spatial domain approach [4], [5]. It directly integrates secret data by substituting the LSBs of the cover image's pixels with secret information bits.…”

Section: A General Contextmentioning

confidence: 99%

Image Steganography by Modified Simple Linear Iterative Clustering

Kich*,

Ameur,

Taouil

2020

IJITEE

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Steganography is an information security technique that consists of concealing secret data into digital medias including videos, texts, network protocols and images. In this paper, a steganography method to dissimulate the secret information in gray-scale images is proposed; the dissimulation is adapted to the cover image’s texture, data is hidden in the edge areas. The edge pixels are selected by over-segmentation using Modified Simple Linear Iterative Clustering (M-SLIC). This algorithm allows to decompose the cover image into K regions which we call superpixels. The image’s texture and the amount of the secret data are the factors that help to determine the value of the parameter K. Choosing the pixels of complex regions to conceal secret information is due to the fact that the human visual system is designed to notice changes in the pixels of smooth areas. Therefore, edge areas tolerate larger changes than smooth areas without causing detectable distortions. Experiment on a large set of images were carried out; results illustrate the good performance of the proposed work in terms of capacity, security and imperceptibility in comparison to recent works.

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“…There are other reliable schemes, such as interpolation [7][8][9]. The essence of the interpolation scheme is to utilize the enlargement of the image resolution.…”

Section: Related Workmentioning

confidence: 99%

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Islamy¹,

Ahmad²

2019

IJIES

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The transmitted information on the internet are prone to security concerns. To overcome this issue, some security methods have been developed in the last few decades. One of the reliable techniques to secure data is called data hiding. This method can be used in various multimedia data, like image, video, text, and audio. Histogram shifting (HS) is a reliable data hiding method used in digital images. It can preserve the similarity of the stego and original image; although, the amount of the protected data depends on the frequency of the most amount pixel in the original image. To solve this problem, we combine HS with prediction error (PE). By using the histogram generated by PE, the size of data that can be embedded increases. In the embedding phase, we do not shift the histogram, different from the existing methods. It is to maintain its original form as high as possible. Moreover, each PE value can contain more data. Based on the experimental result, the average increase in PSNR is 24.8075 dB for general images and 21.5625dB for medical images; while the average improvement of SSIM is 0.026823 and 0.022863 for general and medical images, respectively.

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High capacity data hiding methods based on spline interpolation

Cited by 9 publications

References 17 publications

Enhancing Quality of the Stego Image by Using Histogram Partition and Prediction Error

Enhancing Quality of the Stego Image by Using Histogram Partition and Prediction Error

Image Steganography by Modified Simple Linear Iterative Clustering

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

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