Bilind Identification of Source Cell phone Model

OpenAlex İngilizce

The various image-processing stages in a digital camera pipeline leave telltale footprints, which can be exploited as forensic signatures. These footprints consist of pixel defects, of unevenness of the responses in the CCD sensor, black current noise, and may originate from proprietary interpolation algorithms involved in color filter array [CFA]. Various imaging device (camera, scanner etc.) identification methods are based on the analysis of these artifacts. In this work, we set to explore three sets of forensic features, namely binary similarity measures, image quality measures and higher order wavelet statistics in conjunction with SVM classifier to identify the originating camera. We demonstrate that our camera model identification algorithm achieves more accurate identification, and that it can be made robust to a host of image manipulations. The algorithm has potential to discriminate camera units within the same model.