Digital forensics for printed character source identification

Min-Jen Tsai, Chien Lun Hsu, Jin Sheng Yin, Imam Yuadi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Even digital content is widely used nowadays, printed documents are still ubiquitously accepted and circulated. Therefore, identifying the printed character source is essential for criminal investigations to authenticate the digital copies of the printed documents. This study carefully examines the important statistical features from Gray Level Co-occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT), Spatial filters, Wiener filter, and Gabor filter to identify the printer source for Chinese characters by using support vector machine (SVM) and decision fusion of feature selection. Even the subject of printed Chinese character source identification has been investigated, the proposed technique further expands the feature space which achieves superior experimental results and outperforms the techniques described in the literatures. Therefore, the methodology proposed in this study can accomplish high classification accuracy rate which show promising applications for real world digital forensics.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Multimedia and Expo, ICME 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781467372589
DOIs
StatePublished - 25 Aug 2016
Event2016 IEEE International Conference on Multimedia and Expo, ICME 2016 - Seattle, United States
Duration: 11 Jul 201615 Jul 2016

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
Volume2016-August
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2016 IEEE International Conference on Multimedia and Expo, ICME 2016
CountryUnited States
CitySeattle
Period11/07/1615/07/16

Keywords

  • Discrete Wavelet Transform (DWT)
  • Forensics
  • Gabor Filter
  • Support Vector Machines (SVM)
  • Wiener Filter

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