Abstract

Camera model identification is a hot topic in the field of image forensics. In this paper, a patch-level camera model identification method based on convolutional neural network is proposed. Firstly, inspired by pre-processing method in traditional camera model identification method, an automatic residual extraction module is designed in order to avoid subsequent convolutional neural network being affected by image content. Secondly, a modified SqueezeNet is proposed to extract the camera model related features within image patches. Finally, the effectiveness of the proposed method is verified under a strict patch-level evaluation protocol, which is designed based on the largest public image forensic Dresden database.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.