A Study on Source Device Attribution Using Still Images
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ORIGINAL PAPER
A Study on Source Device Attribution Using Still Images Surbhi Gupta1 · Neeraj Mohan2 · Munish Kumar3 Received: 24 November 2019 / Accepted: 1 June 2020 © CIMNE, Barcelona, Spain 2020
Abstract Images are acquired and stored digitally these days. Image forensics is a science which is concerned with revealing the underlying facts about an image. The universal approaches provide a general strategy to perform image forensics irrespective of the type of manipulation. Identification of acquisition device is one of the significant universal approach. This review paper aims at analyzing the different types of device identification approaches. All research papers aiming camera and mobile detection using image analysis were acquired and then finally 60 most suitable papers were included. Out of these, 32 states of art papers were critically analyzed and compared. As every research starts with the literature review such analysis is significant. This is the first attempt for source camera and source mobile detection evaluation as per the authors knowledge. The authors have concluded that the Accuracy rate of Lens Aberration based detection techniques deteriorates when the different source camera from same brand were under consideration. The performance of color filter array Based Detection techniques dropped when the post processing operation were used on images. These techniques were vulnerable to high compression rate for JPEG images.
1 Introduction to Image Forgery and Forensics An image is a grouping of pixels. These pixels are arranged in rows and column to depict an image in a 2-dimensional structure. Each pixel has some area and intensity value associated with it as exhibited in Fig. 1. Intensity values at respective areas constitute an image. An image processing operation will result in the modification of intensity value of pixels in an image. The amount of change in pixel intensity depends on the image processing procedure. For example, if the brightness of an image needs to be increased or contrast needs to be enhanced; the intensity value of the pixels needs to be altered slightly. While if one object needs to be translated or rotated in the image, then the intensity values of
* Munish Kumar [email protected] 1
Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India
2
Department of Computer Science and Engineering, I.K.G. Punjab Technical University, Mohali Campus, Mohali, Punjab, India
3
Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, India
the pixels need to be changed altogether. An image is characterized by its color depth and resolution. The color depth of an image is controlled by the quantity of bits (k) required to represent an image pixel. Generally, a pixel is represented by 24 bits; 8-bit for each Red, Green and Blue (R, G and B) plane, thus resulting in color depth of 224 colors in the image. Another significant attribute of an
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