JOURNAL ARTICLE
High Embedding Capacity Color Image Steganography Scheme Using Pixel Value Differencing and Addressing the Falling-Off Boundary Problem.
Published In: International Journal of Image & Graphics, 2024, v. 24, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Dharwadkar, Nagaraj V.; Lonikar, Ashutosh A.; Mahmud, Mufti 3 of 3
Abstract
In this paper, we changed the methodology for pixel value differencing. The proposed method work on RGB color images improves the existing PVD technique in terms of embedding capacity and overcomes the issue of falling off boundaries in the traditional PVD technique, and provides security to the secret message from histogram quantization attack. Color images are composed of three different color channels (red, green, and blue), so we cannot apply the traditional pixel value differencing algorithm to them. Due to that, the proposed technique divides the RGB photograph in red, blue, and green channels. Following that the modified pixel value differencing algorithm is employed to all successive pixels of color channels. We get the total embedding capacity by adding the embedding capacities of each color component. After embedding the data, we concatenate the color channels to get the stegoimage. On a series of color images, we tested our pixel value differencing approach and found that the stego-picture's visual excellence and payload capacity were reasonable. The variation in histogram between the stego and cover photographs was minor, making it resistant to histogram quantization attacks, and the suggested approach also solves the issue of falling off the boundary. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Image & Graphics. 2024/07, Vol. 24, Issue 4, p1
- Document Type:Article
- Subject Area:Communication and Mass Media
- Publication Date:2024
- ISSN:0219-4678
- DOI:10.1142/S0219467824500475
- Accession Number:178761476
- Copyright Statement:Copyright of International Journal of Image & Graphics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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