First Steps Toward Camera Model Identification With Convolutional Neural Networks

被引:195
作者
Bondi, Luca [1 ]
Baroffio, Luca [1 ]
Gueera, David [2 ]
Bestagini, Paolo [1 ]
Delp, Edward J. [2 ]
Tubaro, Stefano [1 ]
机构
[1] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy
[2] Purdue Univ, Sch Elect & Comp Engn, Video & Image Proc Lab, W Lafayette, IN 47907 USA
关键词
Camera model identification; convolutional neural networks (CNN); image forensics;
D O I
10.1109/LSP.2016.2641006
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Detecting the camera model used to shoot a picture enables to solve a wide series of forensic problems, from copyright infringement to ownership attribution. For this reason, the forensic community has developed a set of camera model identification algorithms that exploit characteristic traces left on acquired images by the processing pipelines specific of each camera model. In this letter, we investigate a novel approach to solve camera model identification problem. Specifically, we propose a data-driven algorithm based on convolutional neural networks, which learns features characterizing each camera model directly from the acquired pictures. Results on a well-known dataset of 18 camera models show that: 1) the proposed method outperforms up-to-date state-of-the-art algorithms on classification of 64x64 color image patches; 2) features learned by the proposed network generalize to camera models never used for training.
引用
收藏
页码:259 / 263
页数:5
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