Factors that Influence PRNU-Based Camera-Identification via Videos

Abstract

The Photo Response Non-Uniformity pattern (PRNU-pattern) can be used to identify the source of images or to indicate whether images have been made with the same camera. This pattern is also recognized as the “fingerprint” of a camera since it is a highly characteristic feature. However, this pattern, identically to a real fingerprint, is sensitive to many different influences, e.g., the influence of camera settings. In this study, several previously investigated factors were noted, after which three were selected for further investigation. The computation and comparison methods are evaluated under variation of the following factors: resolution, length of the video and compression. For all three studies, images were taken with a single iPhone 6. It was found that a higher resolution ensures a more reliable comparison, and that the length of a (reference) video should always be as high as possible to gain a better PRNU-pattern. It also became clear that compression (i.e., in this study the compression that Snapchat uses) has a negative effect on the correlation value. Therefore, it was found that many different factors play a part when comparing videos. Due to the large amount of controllable and non-controllable factors that influence the PRNU-pattern, it is of great importance that further research is carried out to gain clarity on the individual influences that factors exert.

Three Dimensional Denoising Filter For Effective Source Smartphone Video Identification and Verification

“…In this technique, the PRNUs were estimated from still images obtained by the source device, while the query PRNU is estimated from the video and subsequently linked with the reference to verify the possible match. In [22] , the authors analysed some factors such as compression, resolution and length of the video, which could influence a decrease of the PRNU's correlation value in videos. In [23] , the minimum average correlation energy (MACE) filter [24] was introduced to reduce effect of heavily compressed in low-resolution videos.…”

PRNU Estimation based on Weighted Averaging for Source Smartphone Video Identification

“…In this technique, the reference PRNU was extracted from a number of videos, and then the MACE filter was applied for the reference PRNU to reduce the impact of noises on normalized cross-correlation (NCC). In [25] ,the authors analysed some factors such as resolution, length of the video, and compression, which could influence a decrease of the PRNU's correlation value in videos. While there were several research works attempting to enhance the PRNU estimation for source smartphone video identification, an effective approach that takes into consideration the frame content is still lacking.…”

Sensor Pattern Noise Estimation using Non-textured Video Frames For Efficient Source Smartphone Identification and Verification

“…In this technique, the PRNUs are estimated from still images obtained by the source device, while the query PRNU is estimated from the video and subsequently linked with the reference to verify the possible match. In [20], the authors outlined the possible factors such as Compression, resolution and length of the video, which could influence a decrease of the PRNU's correlation value in videos. Although there have been previous studies [3]- [20] provided in order to improve the efficiency of source smartphone identification based on PRNU, an efficient approach that takes into account the frame content is still lacking.…”

“…In [20], the authors outlined the possible factors such as Compression, resolution and length of the video, which could influence a decrease of the PRNU's correlation value in videos. Although there have been previous studies [3]- [20] provided in order to improve the efficiency of source smartphone identification based on PRNU, an efficient approach that takes into account the frame content is still lacking. Furthermore, existing techniques that consider the effect of lossy compression on the estimation of PRNU in the compressed domain requires full access to the right decoder in order to have separate I-frames at the estimation of the PRNU.…”