Source class identification for DSLR and compact cameras

Yanmei Fang, Ahmet Emir Dirik, Xiaoxi Sun, Nasir Memon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The identification of image acquisition source is an important problem in digital image forensics. In this work, we focus on building a classifier to effectively distinguish between digital images taken from digital single lens reflex (DSLR) and compact cameras. Based on the architecture and the imaging features of DSLR and compact cameras, the images taken from different sources may have different statistical properties in both spatial and transform domains. In this work, we utilized wavelet coefficients and pixel noise statistics to model these two different source classes over 20 different digital cameras. The efficacy of the digital source class identifier, introduced in the paper, has been tested over 1000 high quality camera outputs and post-processed images (resized, re-compressed). Experimental analysis shows that the proposed method has good potential to distinguish DSLR and compact source classes.

Original languageEnglish (US)
Title of host publication2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09
DOIs
StatePublished - 2009
Event2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09 - Rio De Janeiro, Brazil
Duration: Oct 5 2009Oct 7 2009

Publication series

Name2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09

Other

Other2009 IEEE International Workshop on Multimedia Signal Processing, MMSP '09
CountryBrazil
CityRio De Janeiro
Period10/5/0910/7/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing

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