A robust image zero-watermarking using convolutional neural networks

Atoany Fierro-Radilla, Mariko Nakano-Miyatake, Manuel Cedillo-Hernandez, Laura Cleofas-Sanchez, Hector Perez-Meana

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

39 Citas (Scopus)

Resumen

In the image zero-watermarking techniques, a watermark sequence is not physically embedded into the host image but has a logical linkage with the host image. This property of zero-watermarking is desirable for some kinds of images in which a minimum distortion may cause serious detection or diagnostic errors, such as medical images and remote sensing images. In this paper, we propose a robust zero-watermarking algorithm based on the Convolutional Neural Networks (CNN) and deep learning algorithm, in which robust inherent features of image is generated by the CNN, and it is combined with the owner's watermark sequence using XOR operation. The experimental results show the watermark robustness against several attacks and common image processing.

Idioma originalInglés
Título de la publicación alojada2019 7th International Workshop on Biometrics and Forensics, IWBF 2019
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728106229
DOI
EstadoPublicada - may. 2019
Evento7th International Workshop on Biometrics and Forensics, IWBF 2019 - Cancun, México
Duración: 2 may. 20193 may. 2019

Serie de la publicación

Nombre2019 7th International Workshop on Biometrics and Forensics, IWBF 2019

Conferencia

Conferencia7th International Workshop on Biometrics and Forensics, IWBF 2019
País/TerritorioMéxico
CiudadCancun
Período2/05/193/05/19

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