1Blind Identification of Cellular Phone Cameras

In this paper, we focus on blind source cell-phone identification problem. It is known various artifacts in the image processing pipeline, such as pixel defects or unevenness of the responses in the CCD sensor, black current noise, proprietary interpolation algorithms involved in color filter array [CFA] leave telltale footprints. These artifacts, although often imperceptible, are statistically stable and can be considered as a signature of the camera type or even of the individual device. For this purpose, we explore a set of forensic features, such as binary similarity measures, image quality measures and higher order wavelet statistics in conjunction SVM classifier to identify the originating cell-phone type. We provide identification results among 9 different brand cell-phone cameras. In addition to our initial results, we applied a set of geometrical operations to original images in order to investigate how much our proposed method is robust under these manipulations