Abstract
Image integrity authentication has aroused concerns because of the frequent modification on images. However, most of the image authentication schemes proposed so far employed the irreversible data hiding approach and the results of the published few reversible authentication methods are not satisfactory. To improve the detection accuracy as well as marked image quality, this paper proposes an improved reversible image authentication method based on Hilbert Curve mapping. In the proposed method, pixels are first mapped to a one-dimensional vector by using Hilbert Curve and divided into non-overlapping sets. Then, authentication codes can be embedded into each set by reversible data hiding approach. After comparing the extracted bits with the original authentication codes, the image set could be taken as modified one or unmodified one. Because image redundancy can be explored more fully and more flexibly by adopting Hilbert Curve mapping, more authentication codes can be embedded into the host image while leaving less distortion. Thus, both the detection accuracy and the marked image quality can be improved. The experimental results demonstrate the improvement compared with the latest development of reversible image authentication.
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Funding
This study was funded by National Natural Science Foundation of China (Grant Number 61502009 and 61472002), Anhui Provincial Natural Science Foundation (Grant Number 1508085SQF216), Key Program for Excellent Young Talents in Colleges and Universities of Anhui Province (Grant Number gxyqZD2016011), Large-scale Application Demonstration of the Education Cloud (Grant Number 2013BAH72B03) and funds of PADA & CICAEET.
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Zhaoxia Yin, Xuejing Niu, Zhili Zhou, Jin Tang, and Bin Luo declare that they have no conflict of interest.
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All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Additional informed consent was obtained from all patients for which identifying information is included in this article.
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This article does not contain any studies with human or animal subjects performed by the any of the authors.
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Yin, Z., Niu, X., Zhou, Z. et al. Improved Reversible Image Authentication Scheme. Cogn Comput 8, 890–899 (2016). https://doi.org/10.1007/s12559-016-9408-6
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DOI: https://doi.org/10.1007/s12559-016-9408-6