No abstract

Each digital camera has an intrinsic fingerprint that is unique to each camera. This device fingerprint can be extracted from an image and can be compared with a reference device fingerprint to determine the device origin. The complexity of the filters proposed to accomplish this is increasing. In this note, we use a relatively simple algorithm to extract the sensor noise from images. It has the advantages of being easy to implement and parallelize, and working faster than the wavelet filter that is common for this application. In addition, we compare the performance with a simple median filter and assess whether a previously proposed fingerprint enhancement technique improves results. Experiments are performed on approximately 7500 images originating from 69 cameras, and the results are compared with this often used wavelet filter. Despite the simplicity of the proposed method, the performance exceeds the common wavelet filter and reduces the time needed for the extraction.

No abstract

The Photo Response Non-Uniformity acts as a digital fingerprint that can be used to identify image sensors. This characteristic has been used in previous research to identify scanners, digital photo cameras and digital video cameras. In this paper we use a wavelet filter from Lukáš et al [1] to extract the PRNU patterns from multiply compressed low resolution video files originating from webcameras after they have been uploaded to YouTube. The video files were recorded with various resolutions, and the resulting video files were encoded with different codecs. Depending on video characteristics (e.g. codec quality settings, recording resolution), it is possible to correctly identify cameras based on these videos.

No abstract

No abstract

No abstract