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DSLR device determining based on sensor imperfections

Keywords:

Е.А. Aminova – Post-graduate Student, P.G. Demidov Yaroslavl State University
E-mail: lena@piclab.ru
I.N. Trapeznikov – Ph.D. (Eng.), P.G. Demidov Yaroslavl State University
E-mail: trapeznikoff@list.ru
А.L. Priorov – Dr.Sc. (Eng.), Associate Professor, P.G. Demidov Yaroslavl State University
E-mail: andcat@yandex.ru


A detailed investigation of digital images often raises the question of the truth of the observed scene in the tested image. Regardless of its size, it can be false detected by object detection and pattern recognition algorithms as object of interest. Therefore, it is necessary to take into account the sensor imperfections of the digital device that arise during the formation of the digital image processing, which are manifested at various stages of the digital device. In this paper, a method for determining the reliability of obtaining a test image from a guessed device based on the special noise of the photo-fixing device is proposed.
The proposed method is based on the additive model of the information signal consisting of the image under consideration and the object of interest as the sensor imperfections of the device that arise from the uneven response of the sensor pixels to the incident light.
In accordance with the task, the testing of the method in question was carried out on the original digital image base.
As the output criterion of the algorithm, a correlation maximum coefficient was proposed, which is determined by the ratio of the maximum correlation value and the correlation energy of the sensor imperfections, which are extracted from the test image and the noise pattern of the assumed devices for its formation.
To increase the speed of the algorithm, an assessment of the recommended number of images obtained from one digital camera to form a characteristic of the device matrix (15 images) was made.
The algorithm was tested to determine the photo-fixing device from a set of available devices of different models and brands, different models of the same brand and one brand and one model. Verification of a set of test images from the database was also carried out.

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