Isolating lens effects from source camera identification using sensor pattern noise

ABSTRACT

Lens aberrations can be used to determine the provenance of camera optics in an image. However, this method does not necessarily identify the camera itself, since lens systems are often interchanged. A method, first published by Lukàš, Fridrich and Goljan, proposed using Fixed Pattern Noise to link a photo to an image sensor using sensor pattern noise. However, their model did not fully account for lens artefacts or temperature. In our work, we have applied standard image processing theory and an understanding of the geometric properties of light and sensor dark current to continue the isolation of artefacts within the sensor pattern noise model. We use three image sensors to take images using six integrated lenses and prepare reference patterns based on the lens for each camera. We then repeat our experiments with a pinhole lens of our design before comparing the correlation energy contained within each. We show that majority of the unique signal power used to correlate an image to a specific camera is related to the photo response non-uniformity noise; however, additional signal power can also be attributed to the optical system of the camera as well as the sensor’s dark current.

KEYWORDS:

• Sensor pattern noise
• PRNU
• digital forensics
• dark current\

Acknowledgements

This work was supported with supercomputing resources provided by the Phoenix HPC service at the University of Adelaide and is a summary of a thesis chapter.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is supported by an Australian Government Research Training Program (RTP) Scholarship. Additional travel funding was provided by the School of Electrical Engineering at the University of Adelaide to assist with the costs pertaining to accommodation and flights for ANZFSS24.