Securing color information of an image by concealing the color palette

Chaumont, Marc; Puech, William; Lahanier, Christian

doi:10.1016/j.jss.2012.11.042

Cited by 21 publications

(6 citation statements)

References 34 publications

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“…Aside from steganography, good examples of information hiding in images have been explored in [20], [21], [22]. Notably, in these studies, the authors have encoded extra information about the visible image within the transmitted image, for example color information in a gray-scale version of the same image.…”

Section: ç 1 Introductionmentioning

confidence: 99%

Hiding Images within Images

Baluja

2020

IEEE Trans. Pattern Anal. Mach. Intell.

192

107

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We present a system to hide a full color image inside another of the same size with minimal quality loss to either image. Deep neural networks are simultaneously trained to create the hiding and revealing processes and are designed to specifically work as a pair. The system is trained on images drawn randomly from the ImageNet database, and works well on natural images from a wide variety of sources. Beyond demonstrating the successful application of deep learning to hiding images, we examine how the result is achieved and apply numerous transformations to analyze if image quality in the host and hidden image can be maintained. These transformation range from simple image manipulations to sophisticated machine learning-based adversaries. Two extensions to the basic system are presented that mitigate the possibility of discovering the content of the hidden image. With these extensions, not only can the hidden information be kept secure, but the system can be used to hide even more than a single image. Applications for this technology include image authentication, digital watermarks, finding exact regions of image manipulation, and storing meta-information about image rendering and content.

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Section: ç 1 Introductionmentioning

confidence: 99%

Hiding Images within Images

Baluja

2020

IEEE Trans. Pattern Anal. Mach. Intell.

192

107

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“…After generating the color palette and the grayscale image, the color palette should be embedded into the grayscale image for gray-to-color conversation. In the literature, LSB substitution is widely used for embedding color palette, such as [6][7][8][9][10][11][12]. The basic idea of LSB substitution is to substitute the least significant bit of the gray level with the bitstream of the color palette.…”

Section: Reversible Embedding Of the Color Palettementioning

confidence: 99%

“…Invertible conversion from color image to grayscale image is a new technology that ordinary users can only access to grayscale images while privileged users can obtain highquality visualization color images with a secret key. Previous works about invertible conversion from color image to grayscale image are either based on subband embedding (SE) technique [1][2][3][4][5] or vector quantization (VQ) technique [6][7][8][9][10][11][12]. The SE based methods adopt the subband transform techniques and replace the high-frequency subbands with the down-sampled chrominance planes.…”

Section: Introductionmentioning

confidence: 99%

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Invertible Color-to-Grayscale Conversion by Using Clustering and Reversible Watermarking

Liang

Xiang

2021

2021 IEEE International Conference on Multimedia and Expo (ICME)

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Invertible color-to-grayscale conversion is a method that embeds the color information into the corresponding grayscale image and extracts the color information to reconstruct the color image when necessary. In this paper, we propose an efficient method by using K-means clustering to generate a color palette and its corresponding grayscale image, and further making use of a reversible watermarking technique to embed the color palette into the grayscale image. For purpose of integrality authentication, the grayscale image is hashed as part of the embedded information before the embedding. In the process of reconstructing the color image, the color palette can be extracted correctly and the grayscale image can be recovered without any loss. Experimental results have shown that the proposed method can provide satisfactory performance.

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“…Based on a layer scanning algorithm, the color reordering generates gray level images and makes it possible to embed the color palette into the gray level images using a data hiding algorithm. This work was carried out in the framework of a project aimed at providing limited access to the private digital painting database of the Louvre Museum in Paris, France [10].…”

Section: Related Workmentioning

confidence: 99%

An Analysis on LSB Image Steganography with Colour Image as Cover

Chaturvedi¹,

Mohi²

2018

IJCA

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LSB-based steganographic methods embed secret messages into the cover image by directly manipulating the leastsignificant-bit (LSB) plane. Although it is not the best steganographic method, LSB replacement is worth studying because of its large embedding capacity and simplicity. In LSB replacement, the LSB plane is simply replaced with the secret message so that the LSB values carry the hidden message directly. As more and more techniques of hiding information (Steganography) are developed, the methods of detecting the use of steganography (Steganalysis), also advance. Most steganography techniques change the properties of the cover source which increases the probability of detecting the changes. The DCT-M3 algorithm reduces significantly the number of changes in the cover image; the embedding capacity has been improved by 16.7% approximately while maintaining minimum detectability against blind steganalysis schemes. The effectiveness of steganography is measured using three parameters. First, the steganographic technique must provide the maximum information. Second, the embedded data must not be traceable to the viewer. Third, the hidden information should be successfully retrieved at the receiver. It is difficult to recognize the existence of a hidden data in the cover image using the existing methods. This is because embedding is randomly performed in the frequency domain. General TermsSteganography, LSB (Least Significant Bit) image.

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Securing color information of an image by concealing the color palette

Cited by 21 publications

References 34 publications

Hiding Images within Images

Hiding Images within Images

Invertible Color-to-Grayscale Conversion by Using Clustering and Reversible Watermarking

An Analysis on LSB Image Steganography with Colour Image as Cover

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