Blind biometric source sensor recognition using advanced PRNU fingerprints

Previous device identification studies on the iris sensors of the CASIA-Iris V4 database using PRNU fingerprints showed high variations regarding the differentiability of the sensors. These variations may have been caused by the usage of multiple sensors of the same model for the image acquisition. Since no speciic documentation on this exists we investigate the presence of multiple image sensors in the data sets. The images under investigation, furthermore, show a strong correlation regarding their content, therefore we make use of different PRNU enhancements approaches based on weighting the PRNU depending on the image content. The enhanced PRNU is used in conjunction with different forensic techniques to detect the presence of multiple sensors in the data sets. Finally, the results of the enhancement approaches and the results without any PRNU enhancement are compared and an assessment on whether multiple sensor instances have been used in the data sets is given.