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Usage of digital camera identification algorithm for different image parameters


Е.А. Aminova – Post-graduate Student, P.G. Demidov Yaroslavl State University
I.N. Trapeznikov – Ph.D. (Eng.), P.G. Demidov Yaroslavl State University
А.L. Priorov – Dr.Sc. (Eng.), Associate Professor, P.G. Demidov Yaroslavl State University
Yu.A. Bryukhanov – Dr.Sc (Eng.), Professor, P.G. Demidov Yaroslavl State University

In this article, the solution of the authenticity-verifying problem digital image under from the supposed DSLR camera is proposed. This task is considered in the context of the image formation process in digital devices and the arising noise and interference at each stages of this formation. As the basis of the solution, it is proposed to use the structural noise of a digital device, which is unique for each particular device. This type of noise is caused by uneven response of the sensor pixels to the incident light.
Firstly, a unique noise distribution of the structural interference of each device is formed on the basis of several images obtained from device under consideration. Further, based on the correlation analysis, this distribution is compared to that obtained from the test image. Depending on the obtained value of the correlation metric, decisions are made on the formation of a test image by the intended image source.
The dependence of the quality of the proposed algorithm on the parameters of input images is analyzed: the size, the format, the number of images in the set to form the noise distribution, the computing costs of the algorithm and the quality of the JPEG image.
During the testing it was revealed that a sufficient number of images used for the device imperfections distribution without a significant decrease in performance is 15. It is also shown that the algorithm is applicable for various formats and sizes of digital images. Since the JPEG compression format is most often used in modern DSLR devices, the dependence of the correlation metric value on the quality of JPEG compression has been carried out. The steadiness of the algorithm is achieved with quality digital image values from 75% from original relative to the best.
To sum up, the algorithm is applicable for various formats and sizes of digital images.

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