Printed source identification by microscopic images

Min-Jen Tsai, Imam Yuadi

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

The research of printed source identification is generally processed by scanned images which are limited by the scanner resolution. The accuracy of source identification is also bound by this limitation. In this study, microscopic images are used for printed source identification based on its high magnification capability for detailed texture and structure information. 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 features, i.e., Local Binary Pattern (LBP), Gray Level Co-occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT), Spatial filters, Wiener filter, Gabor filter and Haralick filter. Among different set of features, LBP approach achieves the highest identification rate which is significantly superior to other methods. Consequently, the proposed technique using microscopic images achieves high classification accuracy rate which show promising applications for real world digital forensics research.

原文English
主出版物標題2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
發行者IEEE Computer Society
頁面3927-3931
頁數5
ISBN(電子)9781467399616
DOIs
出版狀態Published - 3 8月 2016
事件23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
持續時間: 25 9月 201628 9月 2016

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
2016-August
ISSN(列印)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
國家/地區United States
城市Phoenix
期間25/09/1628/09/16

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