Robustness in blind camera identification

In this paper, we focus on studying the effects of various image operations on sensor fingerprint camera identification. It is known that artifacts in the image processing pipeline, such as pixel defects or unevenness of the responses in the CCD array as well black current noise leave telltale footprints. Nowadays, camera identification based on the analysis of these artifacts is a well established technology for linking an image to a specific camera. The sensor fingerprint is estimated from images taken from a device. A similarity measure is deployed in order to associate an image with the camera. However, when the images used in the sensor fingerprint estimation have been processed using e.g. gamma correction, contrast enhancement, histogram equalization or white balance, the properties of the detection statistic change, hence affecting fingerprint detection. In this paper we study this effect experimentally, towards quantifying the robustness of fingerprint detection in the presence of image processing operations.