Identifying Images Corrected for Lens Distortion Using Sensor Fingerprints
| Type of publication: | Inproceedings |
| Citation: | goljan-fridrich-spie12 |
| Booktitle: | SPIE Conference on Media Waternarking, Security, and Forensics |
| Year: | 2012 |
| Location: | San Francisco, CA |
| Abstract: | Computational photography is quickly making its way from professional devices to consumer cameras. Recently, camera manufacturers started using in-camera lens-distortion correction of the captured image to give users more powerful range of zoom in compact and affordable cameras. Since the distortion correction (barrel/pincushion) depends on the zoom, it desynchronizes the pixel-to-pixel correspondence between images taken at two different focal lengths. This poses a serious problem for digital forensic techniques that utilize the concept of sensor fingerprint (photo-response non-uniformity), such as "image ballistic" techniques that can match an image to a specific camera in a similar manner as a bullet can be matched to a gun barrel. Such identification techniques may in fact completely fail. This paper presents an extension of sensor-based camera identification that would work for images whose content was corrected for lens distortion. To reestablish synchronization between an image and the fingerprint, we adopt a barrel distortion model and search for its parameters to maximize the detection statistic, which is the PCE (peak to correlation energy ratio). The proposed method is tested on hundreds of images from three compact cameras to prove the viability of the concept and demonstrate its efficiency. |
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| Added by: | [ADM] |
| Total mark: | 0 |
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