CFA pattern identification of digital cameras using intermediate value counting

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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