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In digital image forensics, estimating the color filter array (CFA) pattern can be useful for digital camera identification. In this paper, we proposed the new method to estimate the CFA pattern of the digital cameras from a single image. Our method is based on the basic principal of CFA interpolation which fills an empty pixel using neighbor pixels. For each channel, we define the specific neighbor pattern and count the intermediate values. The CFA pattern is estimated by utilizing this counting information of three channels. The experimental results show that the proposed method achieves high accuracy with various camera models and CFA interpolation algorithms.

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Numerous forgeries are made by precise and fast colour laser printers, and they have the ability to cause severe harm to society. To prevent such forgeries, printer identification can be employed as a countermeasure. A new method is presented to identify colour laser printers using halftone texture fingerprints. The method uses images photographed without an additional close-up lens as input images, and halftone texture fingerprints are extracted in the curvelet transform domain. The extracted halftone texture fingerprint is used in correlation-based detection, and the colour laser printer of the most similar known halftone texture fingerprint is determined as the source colour laser printer. Experiments are performed on five colour laser printers and the performance is compared with existing methods. Experimental results show that the method overcomes the limitations of existing methods.