Title :
Camera model identification framework using an ensemble of demosaicing features
Author :
Chen Chen;Matthew C. Stamm
Author_Institution :
Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA 19104, United States of America
Abstract :
Existing approaches to camera model identification frequently operate by building a parametric model of a camera component, then using an estimate of these model parameters to identify the source camera model. Since many components in a camera´s processing pipeline are both complex and nonlinear, it is often very difficult to build these parametric models or improve their accuracy. In this paper, we propose a new framework for identifying the model of an image´s source camera. Our framework builds a rich model of a camera´s demosaicing algorithm inspired by Fridrich et al.´s recent work on rich models for steganalysis. We present experimental results showing that our framework can identify the correct make and model of an image´s source camera with an average accuracy of 99.2%.
Keywords :
"Cameras","Image color analysis","Parametric statistics","Algorithm design and analysis","Interpolation","Buildings","Pipelines"
Conference_Titel :
Information Forensics and Security (WIFS), 2015 IEEE International Workshop on
DOI :
10.1109/WIFS.2015.7368573