Temporal forensic analysis of digital Camera sensor imperfections for picture dating

The research proposal aims to investigate the temporal variations of camera sensor imperfections in order to establish, for any given digital camera, a theoretical model that allows the analyst to estimate the acquisition date of digital pictures. This will advance the field of forensic science, with the potential for applications in high profile cases that require the extraction of evidential information for courtroom purposes. In this project, the analyst is assumed to have the camera device or a set of trusted pictures taken by the same camera and whose acquisition time is known. The goal is then to date one or more images supposedly obtained from the same source and whose acquisition time is unknown. This application will obviously help forensic investigators analyse incidents and link different events.
The novelty of the proposed approach lies in (i) New techniques for efficiently estimating the sensor pattern noise for the purpose of temporal analysis (ii) Classification and temporal analysis of three types of pixels, namely, normal pixels, abnormal but not yet defective pixels, and defective pixels. (iii) Use of machine learning techniques to model the temporal behaviour of camera sensor imperfections.

This proposed research would be of great help to forensic scientists and investigators in police forces throughout the UK and beyond since the extraction of informaion from digital images can be used for courtroom purposes. It should also have a positive economic impact in future by enabling the leading UK industrial companies to develop internationally competitive products for picture dating as this has not yet been considered in the UK and elsewhere. In a local context, we will transfer the skills and techniques gained during our investigation to other group members in the Conputer and Electronic security Systems Lab at Northumbria University and to our collaborators in this project.

The results of this research project will be disseminated to the research community through publications at key international conferences and in high impact journals. Furthermore, under the main CESS website, a new webpage will be designed and updated regularly during the project for providing up-to-date details, experimental results, and free access to the standard dataset.