Abstract
With the rapid development of network technology, concerns pertaining to the enhancement of security and protection against violations of digital images have become critical over the past decade. In this paper, an image copy detection scheme based on the Inception convolutional neural network (CNN) model in deep learning is proposed. The image dataset is transferred by a number of image processing manipulations and the feature values in images are automatically extracted for learning and detecting the suspected unauthorized digital images. The experimental results show that the proposed scheme takes on an extraordinary role in the process of detecting duplicated images with rotation, scaling, and other content manipulations. Moreover, the mechanism of detecting duplicate images via a convolutional neural network model with different combinations of original images and manipulated images can improve the accuracy and efficiency of image copy detection compared with existing schemes.
Highlights
Multimedia forensics is one of the key technologies for digital evidence authentication in cybersecurity
An image copy detection scheme based on the Inception V3 convolutional neural network is proposed in this paper
The image dataset is firstly transferred by a number of image processing manipulations for training the detection model with feature values
Summary
Multimedia forensics is one of the key technologies for digital evidence authentication in cybersecurity. The rapid expansion in the amount of digital content in social networks has brought about a significant increase in the number of copyright infringements [1]. New image processing manipulations are rapidly developing and are incorporated into image processing software such as Photo Impact and Adobe Photoshop. Digital images are more likely to be copied and tampered while transmitting over the Internet. Concerns pertaining to the enhancement of security and protection against violations of digital images have become critical over the past decade [2]. Researchers are devoted to designing associated forensics algorithms, detecting the unauthorized manipulation, and protecting the copyrights of original images
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