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Sensors 2018, 18(10), 3372; https://doi.org/10.3390/s18103372

Digital Images Authentication Technique Based on DWT, DCT and Local Binary Patterns

1
Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, 28040 Madrid, Spain
2
School of Computing, Office S129A, University of Kent, Cornwallis South Building, Canterbury CT2 7NF, UK
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 19 August 2018 / Revised: 26 September 2018 / Accepted: 30 September 2018 / Published: 9 October 2018
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Abstract

In the last few years, the world has witnessed a ground-breaking growth in the use of digital images and their applications in the modern society. In addition, image editing applications have downplayed the modification of digital photos and this compromises the authenticity and veracity of a digital image. These applications allow for tampering the content of the image without leaving visible traces. In addition to this, the easiness of distributing information through the Internet has caused society to accept everything it sees as true without questioning its integrity. This paper proposes a digital image authentication technique that combines the analysis of local texture patterns with the discrete wavelet transform and the discrete cosine transform to extract features from each of the blocks of an image. Subsequently, it uses a vector support machine to create a model that allows verification of the authenticity of the image. Experiments were performed with falsified images from public databases widely used in the literature that demonstrate the efficiency of the proposed method. View Full-Text
Keywords: digital images; discrete cosine transforms; forgery detection; image forensics; images splicing; local pattern binary; support vector machines; wavelet transforms digital images; discrete cosine transforms; forgery detection; image forensics; images splicing; local pattern binary; support vector machines; wavelet transforms
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Armas Vega, E.A.; Sandoval Orozco, A.L.; García Villalba, L.J.; Hernandez-Castro, J. Digital Images Authentication Technique Based on DWT, DCT and Local Binary Patterns. Sensors 2018, 18, 3372.

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