Open Access

ARTICLE

Reversible Data Hiding Based on Varying Radix Numeral System

J. Hemalatha¹, S. Geetha², R. Geetha³, C. Balasubramanian⁴, Daniela Elena Popescu⁵, D. Jude Hemanth^6,*
1 AAA College of Engineering and Technology, Sivakasi, India
2 SCOPE, VIT University, Chennai, India
3 SENSE, VIT University, Chennai, India
4 Department of CSE, Kalasalingam Academy of Research and Education, India
5 Faculty of Electrical Engineering and Information Technology, University of Oradea, Oradea, Romania
6 Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India
* Corresponding Author: D. Jude Hemanth. Email:
(This article belongs to this Special Issue: Advanced signal acquisition and processing for Internet of Medical Things)

Computers, Materials & Continua 2021, 69(1), 283-300. https://doi.org/10.32604/cmc.2021.017203

Received 23 January 2021; Accepted 25 March 2021; Issue published 04 June 2021

Abstract

A novel image reversible data-hiding scheme based on primitive and varying radix numerical model is presented in this article. Using varying radix, variable sum of data may be embedded in various pixels of images. This scheme is made adaptive using the correlation of the neighboring pixels. Messages are embedded as blocks of non-uniform length in the high-frequency regions of the rhombus mean interpolated image. A higher amount of data is embedded in the high-frequency regions and lesser data in the low-frequency regions of the image. The size of the embedded data depends on the statistics of the pixel distribution in the cover image. One of the major issues in reversible data embedding, the location map, is minimized because of the interpolation process. This technique, which is actually LSB matching, embeds only the residuals of modulo radix into the LSBs of each pixel. No attacks on this RDH technique will be able to decode the hidden content in the marked image. The proposed scheme delivers a prominent visual quality despite high embedding capacity. Experimental tests carried out on over 100 natural image data sets and medical images show an improvement in results compared to the existing schemes. Since the algorithm is based on the variable radix number system, it is more resistant to most of the steganographic attacks. The results were compared with a higher embedding capacity of up to 1.5 bpp reversible schemes for parameters like Peak Signal-to-Noise Ratio (PSNR), Embedding Capacity (EC) and Structural Similarity Index Metric (SSIM).

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Keywords

Data hiding; spatial correlation; radix system; prediction error; embedding capacity

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