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The problem investigated in this paper is identification of sensor that was used to obtain a given digital image. We show that the high-medium frequency component of the sensor pattern noise is an equivalent of "bullet scratches" for digital images and can be used for reliable forensic identification. For each sensor, we first calculate its reference pattern (an estimate of the sensor pattern noise) by averaging the noise component from multiple images. This pattern serves as a unique identification fingerprint whose presence in a given image is established using a correlation detector. The proposed identification technique was tested on several thousand images obtained by nine digital cameras. In all cases, we were able to correctly identify the camera that took the image. We also show that it is possible to identify the camera from images subjected to combined processing, including lossy JPEG compression, gamma correction, recoloring, and resizing.