Camera brand and model identification using moments of 1-D and 2-D characteristic functions

Guanshuo Xu, Yun Qing Shi, Wei Su

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

7 Scopus citations

Abstract

Camera brand and model identification has become one important task of image forensics. Most of the research on this topic focuses on only one or two parts of camera inner structure. In this paper, we propose a universal image statistical model which takes the whole image formation pipeline of cameras into consideration. By examining their comprehensive effects on the formulated images, our assumption is that any difference of the parts of the image formation pipeline can result in the statistical difference of the output image. Moments of 1-D characteristic functions generated from the given image, its JPEG 2-D array, their prediction-error 2-D arrays, and all of their three-level wavelet subbands, and moments of 2-D characteristic functions generated only from JPEG 2-D array accordingly are used to build the statistical model for classification. Our experimental works have verified the effectiveness of this proposed method.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Pages2917-2920
Number of pages4
ISBN (Print)9781424456543
DOIs
StatePublished - Jan 1 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: Nov 7 2009Nov 10 2009

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2009 IEEE International Conference on Image Processing, ICIP 2009
CountryEgypt
CityCairo
Period11/7/0911/10/09

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Keywords

  • Camera identification
  • Moments of characteristic functions

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