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Multimedia Tools and Applications

, Volume 77, Issue 7, pp 8729–8758 | Cite as

Digital forensics of microscopic images for printed source identification

  • Min-Jen Tsai
  • Imam Yuadi
Article
  • 295 Downloads

Abstract

When trying to identify a printed forged document, examining digital evidence can prove to be a challenge. In this study, microscopic images are used for printed source identification due to their high magnification properties resulting in detailed texture and structure information. Prior research implemented a scanner as a digitizing technique to resolve very fine printed identification, but this technique provided limited information on the resolution and magnification of the sample. In contrast, the performance of microscopy techniques can retrieve the shape and surface texture of a printed document with differing micro structures among printer sources. To explore the relationship between source printers and images obtained by the microscope, the proposed approach utilizes image processing techniques and data exploration methods to calculate many important statistical features, including: Local Binary Pattern (LBP), Gray Level Co-occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT), Spatial filters, the Wiener filter, the Gabor filter, Haralick, and SFTA features. Among the different set of features, the LBP approach achieves the highest identification rate and is significantly superior to other methods. As a result, the proposed technique using microscopic images achieves a high classification accuracy rate, which shows promising applications for real world digital forensics research.

Keywords

Microscopic images Digital image forensics Feature filters Support vector machines (SVM) Local binary pattern (LBP) 

Notes

Acknowledgments

This work was partially supported by the National Science Council in Taiwan, Republic of China, under NSC104-2410-H-009-020-MY2.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Institute of Information ManagementNational Chiao Tung UniversityHsin-ChuRepublic of China
  2. 2.Department of Information and Library ScienceAirlangga UniversitySurabayaIndonesia

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