Camera sensor identification for biometric images
Photo Response Non-Uniformity (PRNU) has been successfully utilized for sensor identification in the literature and is important in the context of image forensics. PRNU manifests as a consequence of artifacts associated with the sensor fabrication process. In iris biometrics, the images are captured using iris sensors typically operating in the near-infrared spectrum, which differ from conventional RGB sensors employed in the camera. Also, the iris images can be subjected to some pre-processing schemes, such as photometric modifications to aid in iris recognition. We evaluate different PRNU schemes in the context of iris sensor identification. We further analyze the impact of photometric transformations known to improve iris recognition performance on PRNU based sensor identification.
In many image forensic applications, one can implicitly link the camera with the photographer. This raises privacy concerns, which can be mitigated via sensor de-identification. In this context, we deliberately perturb the image such that the PRNU based sensor classifier incorrectly assigns the modified image to a different sensor but without compromising the utility of the images. In our work, we aim to confound the iris sensor classifier, whilst preserving the iris recognition performance.
S. Banerjee, V. Mirjalili, A. Ross, “Spoofing PRNU Patterns of Iris Sensors while Preserving Iris Recognition,” Proc. of 5th IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), (Hyderabad, India), January 2019.
S. Banerjee and A. Ross, "Impact of Photometric Transformations on PRNU Estimation Schemes: A Case Study Using Near Infrared Ocular Images," Proc. of 6th IAPR/IEEE International Workshop on Biometrics and Forensics, (Sassari, Italy), June 2018.
S. Banerjee and A. Ross, "From Image to Sensor: Comparative Evaluation of Multiple PRNU Estimation Schemes for Identifying Sensors from NIR Iris Images," 5th International Workshop on Biometrics and Forensics (IWBF), (Coventry, UK), April 2017.
S. Banerjee and A. Ross, “Smartphone Camera De-identification while Preserving Biometric Utility,” Proc. of 10th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Tampa, USA), September 2019.