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Special Issue "Camera Identification on Mobile Devices"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 15 December 2019.

Special Issue Editors

Prof. Dr. Modesto Castrillón Santana
E-Mail Website
Guest Editor
SIANI, Universidad de Las Palmas de Gran Canaria, Spain
Interests: face detection; facial analysis; soft biometrics; local descriptors; human computer interaction
Prof. Dr. Javier Lorenzo-Navarro
E-Mail Website
Guest Editor
SIANI, Universidad de Las Palmas de Gran Canaria, Spain
Interests: facial analysis; soft biometrics; local descriptors; human computer interaction; data mining

Special Issue Information

Dear Colleagues,

Given the everyday decreasing cost of digital imaging devices, there is a non-stop larger presence of digital content in people’s daily lives, not just as consumers, but also as producers. In fact, we are immersed in a massive explosion of digital media availability, which collaterally imposes the need for fast, reliable and inexpensive data origin identification or authentication. This fact is becoming more relevant considering
the daily increasing population belonging digital embedded cameras, such as smartphones, and producing and sharing media on the Internet. However, the existence of a larger community, comprises also an increasing number of situations of improper use. In this sense, researchers have shown a particular interest in the camera identification problem for forensic investigations, i.e., considering its utility as evidence or silent witness in court. While developing more robust solutions in real world scenarios is a must, criminals also become aware of image forensics possibilities, thus there is an additional need to cope with malicious  manipulation of images with the aim of spoofing sensor identification, i.e., to guarantee the sensor origin.

This Special Issue invites researchers to focus on this particular problem in the context of mobile devices defining state-of-the-art solutions for real-world applications, in the wild benchmarks, new applications, or critical surveys.

 

Prof. Dr. Modesto Castrillón Santana
Prof. Dr. Javier Lorenzo-Navarro
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Source camera identification
  • Camera sensor identification
  • Camera model identification
  • Source device linking
  • Digital forensics
  • Photo-response non-uniformity
  • Sensor fingerprint
  • Doctored images detection
  • Spoofing camera identirfication
  • Blind image clustering of unknown source sensors
  • Classification of images taken by un-known cameras

Published Papers (2 papers)

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Research

Open AccessArticle
Hybrid reference-based Video Source Identification
Sensors 2019, 19(3), 649; https://doi.org/10.3390/s19030649 - 05 Feb 2019
Cited by 1
Abstract
Millions of users share images and videos generated by mobile devices with different profiles on social media platforms. When publishing illegal content, they prefer to use anonymous profiles. Multimedia Forensics allows us to determine whether videos or images have been captured with the [...] Read more.
Millions of users share images and videos generated by mobile devices with different profiles on social media platforms. When publishing illegal content, they prefer to use anonymous profiles. Multimedia Forensics allows us to determine whether videos or images have been captured with the same device, and thus, possibly, by the same person. Currently, the most promising technology to achieve this task exploits unique traces left by the camera sensor into the visual content. However, image and video source identification are still treated separately from one another. This approach is limited and anachronistic, if we consider that most of the visual media are today acquired using smartphones that capture both images and videos. In this paper we overcome this limitation by exploring a new approach that synergistically exploits images and videos to study the device from which they both come. Indeed, we prove it is possible to identify the source of a digital video by exploiting a reference sensor pattern noise generated from still images taken by the same device. The proposed method provides performance comparable with or even better than the state-of-the-art, where a reference pattern is estimated from video frames. Finally, we show that this strategy is effective even in the case of in-camera digitally stabilized videos, where a non-stabilized reference is not available, thus solving the limitations of the current state-of-the-art. We also show how this approach allows us to link social media profiles containing images and videos captured by the same sensor. Full article
(This article belongs to the Special Issue Camera Identification on Mobile Devices)
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Open AccessArticle
A New Dataset for Source Identification of High Dynamic Range Images
Sensors 2018, 18(11), 3801; https://doi.org/10.3390/s18113801 - 06 Nov 2018
Cited by 2
Abstract
Digital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In [...] Read more.
Digital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In this paper, we present a novel database of HDR and SDR images captured in different conditions, including various capturing motions, scenes and devices. As a possible application of this dataset, the performance of the well-known reference pattern noise-based source identification algorithm was tested on both kinds of images. Results have shown difficulties in source identification conducted on HDR images, due to their complexity and wider dynamic range. It is concluded that capturing conditions and devices themselves can have an impact on source identification, thus leaving space for more research in this field. Full article
(This article belongs to the Special Issue Camera Identification on Mobile Devices)
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