Discrete cosine transform and hash functions toward implementing a (robust-fragile) watermarking scheme

Saeed Al-Mansoori; Alavi Kunhu

doi:10.1117/12.2029163

23 October 2013 Discrete cosine transform and hash functions toward implementing a (robust-fragile) watermarking scheme

Saeed Al-Mansoori, Alavi Kunhu

Proceedings Volume 8895, High-Performance Computing in Remote Sensing III; 889504 (2013) https://doi.org/10.1117/12.2029163
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

This paper proposes a blind multi-watermarking scheme based on designing two back-to-back encoders. The first encoder is implemented to embed a robust watermark into remote sensing imagery by applying a Discrete Cosine Transform (DCT) approach. Such watermark is used in many applications to protect the copyright of the image. However, the second encoder embeds a fragile watermark using ‘SHA-1’ hash function. The purpose behind embedding a fragile watermark is to prove the authenticity of the image (i.e. tamper-proof). Thus, the proposed technique was developed as a result of new challenges with piracy of remote sensing imagery ownership. This led researchers to look for different means to secure the ownership of satellite imagery and prevent the illegal use of these resources. Therefore, Emirates Institution for Advanced Science and Technology (EIAST) proposed utilizing existing data security concept by embedding a digital signature, “watermark”, into DubaiSat-1 satellite imagery. In this study, DubaiSat-1 images with 2.5 meter resolution are used as a cover and a colored EIAST logo is used as a watermark. In order to evaluate the robustness of the proposed technique, a couple of attacks are applied such as JPEG compression, rotation and synchronization attacks. Furthermore, tampering attacks are applied to prove image authenticity.

Citation Download Citation

Saeed Al-Mansoori and Alavi Kunhu "Discrete cosine transform and hash functions toward implementing a (robust-fragile) watermarking scheme", Proc. SPIE 8895, High-Performance Computing in Remote Sensing III, 889504 (23 October 2013); https://doi.org/10.1117/12.2029163

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