04-06-2013, 12:47 PM
Colour-Decoupled Photo Response Non-Uniformity for Digital Image Forensics
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Abstract
The last few years have seen the use of photo response non-uniformity noise (PRNU), a unique fingerprint of imaging sensors, in various digital forensic applications such as source device identification, content integrity verification and authentication. However, the use of a colour filter array for capturing only one of the three colour components per pixel introduces colour interpolation noise, while the existing methods for extracting PRNU provide no effective means for addressing this issue. Because the artificial colours obtained through the colour interpolation process is not directly acquired from the scene by physical hardware, we expect that the PRNU extracted from the physical components, which are free from interpolation noise, should be more reliable than that from the artificial channels, which carry interpolation noise. Based on this assumption we propose a Couple-Decoupled PRNU (CD-PRNU) extraction method, which first decomposes each colour channel into 4 sub-images and then extracts the PRNU noise from each sub-image. The PRNU noise patterns of the sub-images are then assembled to get the CD-PRNU. This new method can prevent the interpolation noise from propagating into the physical components, thus improving the accuracy of device identification and image content integrity verification.
INTRODUCTION
S digital multimedia processing hardware and software become more affordable and their functionalities become more versatile, their use in our everyday life becomes ubiquitous. However, while most of us enjoy the benefits these technologies have to offer, the very same set of technologies can also be exploited to manipulate contents for malicious purposes. Consequently, the credibility of digital multimedia when used as evidence in legal and security domains will be constantly challenged and has to be scientifically proved. After over 15 years of intensive research, digital watermarking [1, 2, 3, 4, 5, 6, 7] has been accepted as an effective way of verifying content integrity in a wide variety of applications and will continue to play an important role in multimedia protection and security.
Photo Response Non-Uniformity (PRNU)
Among so many types of intrinsic device signatures, sensor pattern noise [11, 14, 19, 20, 28] have drawn much attention due to its feasibility in identifying not only device models of the same make, but also individual devices of the same model [9, 11, 14]. Sensor pattern noise is mainly caused by imperfections during the manufacturing process of semiconductor wafers and slight variations in which individual sensor pixels convert light to electrical signal [29]. It is this uniqueness of manufacturing imperfections and non-uniformity of photo-electronic conversion that makes sensor pattern noise capable of identifying imaging sources to the accuracy of individual devices. The reader is referred to [29] for more details in relation to sensor pattern noise.
DEMOSAICKING IMPACT ON PRNU FIDELITY
In this work, we call the colour components physically
captured by the sensor as physical colours and the ones
artificially interpolated by the demosaicking function as
artificial colours. Due to the fact that demosaicking is a key
deterministic process that affects the quality of colour images
taken by many digital devices, demosaicking has been
rigorously investigated [31, 32, 33, 35, 36]. Most
demosaicking approaches group the missing colours before
applying an interpolation function. The grouping process is
usually content-dependent, e.g., edge-adaptive or nonadaptive,
hence the accuracy of colour interpolation result is
also content-dependent [37]. For example, in a homogeneous
area, because of the low variation of the colour intensities of
neighbouring pixels, the interpolation function can more
accurately generate artificial components [30]. Conversely, in
inhomogeneous areas, the colour variation between
neighbouring pixels is greater, thus the interpolation noise is
also more significant.
Experiment on Image III.3
When authenticating III.3, although the performance of
PRNU and CD-PRNU in terms of TN and FP are mixed, as
can be seen in Figure 11(b) and 11©, CD-PRNU‟s
significantly better performance in terms of TP and lower FN
can still be seen again in Figure 11(a) and 11(d), respectively.
When the threshold t is higher than 1.1, the PRNU cannot
correctly detect any manipulated blocks (i.e., TP 0 as
demonstrated in Figure 11(a)). This poor performance is also
reflected in the PRNU‟s ROC curve in Figure 12 and is due to
the fact that he manipulated area is too small (60 × 80 pixels),
which is only about one quarter of the sliding window (128 ×
128 pixels). Chen predicated in [11] that one quarter of the
sliding window is the lower bound on the size of tampered
regions that our algorithm can identify, and therefore areas
smaller than this should be filtered in order to remove the
falsely identified noise. The experiment result on III.3
conforms to Chen‟s observation
CONCLUSION
In this work we have pointed out that the use of a colour filter array (CFA) in the image acquisition process can lead to inaccurate extraction of the PRNU, a commonly used fingerprint for identifying source imaging devices and image authentication. We have also proposed a simple, yet effective, colour-decoupled PRNU (CD-PRNU) extraction method, which can prevent the CFA interpolation error from diffusing from the artificial colour channels into the physical channels, thus improving the accuracy of the fingerprint. Moreover, the proposed method requires no a priori knowledge about the CFA colour configuration. Experiments on source camera identification and content integrity verification have been carried out to test our proposed CD-PRNU extraction method and significant improvement has been confirmed.