Comparison of PRNU enhancement techniques to generate PRNU fingerprints for biometric source sensor attribution

Abstract

Identifying the source camera which acquired a given image using the cameras PRNU is a well established task in image forensics, known as camera or device identification. Since digital image sensors are widely used to acquire biometric data, it is eligible that this task can also be performed with biometric sensors and the respective data. This has already been studied in literature. In this paper we focus on a slightly different task, which consists in clustering images acquired with the same sensor in a data set possibly containing images from an unknown number of biometric sensors. Previous work showed unclear results that have been difficult to interpret because of the low quality of the extracted PRNU. In this paper we compare the use of a PRNU enhancement technique to the use of special uncorrelated images acquired with known biometric sensors in this clustering context. We additionally propose extensions of existing source sensor attribution techniques using data from known sensors. Finally, the results of the enhancement approaches and the results using the uncorrelated data acquired with the known sensors are compared and an assessment on whether multiple sensor instances have been used in the different investigated data sets is given.