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Source camera identification using non-decimated wavelet transform

  • Ahmad Ryad Soobhany*
  • , Akbar Sheikh-Akbari
  • , Z. Cliffe Schreuders
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Source Camera identification of digital images can be performed by matching the sensor pattern noise (SPN) of the images with that of the camera reference signature. This paper presents a non-decimated wavelet based source camera identification method for digital images. The proposed algorithm applies a non-decimated wavelet transform on the input image and split the image into its wavelet sub-bands. The coefficients within the resulting wavelet high frequency sub-bands are filtered to extract the SPN of the image. Cross correlation of the image SPN and the camera reference SPN signature is then used to identify the most likely source device of the image. Experimental results were generated using images of ten cameras to identify the source camera of the images. Results show that the proposed technique generates superior results to that of the state of the art wavelet based source camera identification.

Original languageEnglish
Title of host publicationGlobal Security, Safety and Sustainability: The Security Challenges of the Connected World
Subtitle of host publication11th International Conference, ICGS3 2017, London, UK, January 18-20, 2017, Proceedings
EditorsHamid Jahankhani, Alex Carlile, David Emm, Amin Hosseinian-Far, Guy Brown, Graham Sexton, Arshad Jamal
Pages125-133
Number of pages9
ISBN (Electronic)9783319510644
DOIs
Publication statusPublished - 4 Jan 2017
Event11th International Conference on Global Security, Safety, and Sustainability 2017 - London, United Kingdom
Duration: 18 Jan 2017 → 20 Jan 2017

Publication series

NameCommunications in Computer and Information Science
Volume630
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference11th International Conference on Global Security, Safety, and Sustainability 2017
Abbreviated titleICGS3 2017
Country/TerritoryUnited Kingdom
CityLondon
Period18/01/17 → 20/01/17

Keywords

  • Digital forensics
  • Non-decimated wavelet transform
  • PRNU
  • Sensor pattern noise
  • Source identification
  • SPN

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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