Order reprints

A batch copyright scheme for digital image based on deep neural network

Haoyu Lu Daofu Gong Fenlin Liu Hui Liu Jinghua Qu

*Corresponding author: Daofu Gong gongdf@aliyun.com


Digital signature and watermarking are effective image copyright protection techniques. However, these methods come with some inherent drawbacks, including the incapacity of carrying information and inevitable fidelity loss, respectively. To improve this situation, this paper proposes a neural network-based image batch copyright protection scheme, with which a copyright message bitstream can be extracted from each registered image while no modifications are introduced. Taking advantage of the pattern extraction capability and the error tolerance of the neural network, the proposed scheme achieves perfect imperceptibility and superior robustness. Moreover, the network’s preference for diverse data content makes it especially appropriate for multiple images copyright verification. These claims will be further supported by the experimental results in this paper.

Please supply your name and a valid email address you yourself

Fields marked*are required

Article URL   http://www.aimspress.com/MBE/article/3917.html
Article ID   mbe-16-05-306
Editorial Email  
Your Name *
Your Email *
Quantity *

Copyright © AIMS Press All Rights Reserved