An efficient image tamper detection and self-recovery scheme using rehashing model based digital watermarking

Xuejing Li; Yonglong Luo; Weixin Bian; Haiyan Zhang

doi:10.1117/12.2600985

30 June 2021 An efficient image tamper detection and self-recovery scheme using rehashing model based digital watermarking

Xuejing Li, Yonglong Luo, Weixin Bian, Haiyan Zhang

Author Affiliations +

Proceedings Volume 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021); 1187812 (2021) https://doi.org/10.1117/12.2600985
Event: Thirteenth International Conference on Digital Image Processing, 2021, Singapore, Singapore

Abstract

Image tamper detection techniques have been proposed to address the potential tampering problems of image content, as digital images can be easily modified, diffused, transformed and duplicated via the Internet. In order to achieve high detection successful rate and self-recovery accuracy in image tamper areas, an efficient scheme of rehashing model based digital watermarking for image tamper detection and self-recovery is proposed in this study. The rehashing model consists of a series of random hash functions, which is presented to avoid numerous random number collisions that embrace the authentication data for image tamper detection and self-recovery. Additionally, these authentication data can be further embedded into the original image as digital watermarking by means of the constructed two-dimensional reference matrix. The experimental results demonstrate that this novel scheme outperforms the other related works in terms of tamper area localization and self-recovery accuracy; moreover, the proposed image tamper detection and self-recovery technique can obtain an acceptable recovery image visual quality with half image content tamper.

Citation Download Citation

Xuejing Li, Yonglong Luo, Weixin Bian, and Haiyan Zhang "An efficient image tamper detection and self-recovery scheme using rehashing model based digital watermarking", Proc. SPIE 11878, Thirteenth International Conference on Digital Image Processing (ICDIP 2021), 1187812 (30 June 2021); https://doi.org/10.1117/12.2600985

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