Source Identification for Printed Documents

Min-Jen Tsai, Mam Yuadi, Yu Han Tao, Jin Sheng Yin

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

Technological advances in digitization with a variety of image manipulation techniques enable the creation of printed documents illegally. Correspondingly, many researchers conduct studies in determining whether the document printed counterfeit or original. This study examines the several statistical feature sets from Gray Level Co-occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT), Spatial filters, Wiener filter, Gabor filter, Haralick and fractal filters to identify text and image document by using support vector machine (SVM) and decision fusion of feature selection. The average experimental results achieves that the image document is higher identification rate than text document. In summary, the proposed method outperforms the previous researches and it is a promising technique that can be implemented in real forensics for printed documents.

原文English
主出版物標題Proceedings - 2017 IEEE 3rd International Conference on Collaboration and Internet Computing, CIC 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面54-58
頁數5
ISBN(電子)9781538625651
DOIs
出版狀態Published - 9 十二月 2017
事件3rd IEEE International Conference on Collaboration and Internet Computing, CIC 2017 - San Jose, United States
持續時間: 15 十月 201717 十月 2017

出版系列

名字Proceedings - 2017 IEEE 3rd International Conference on Collaboration and Internet Computing, CIC 2017
2017-January

Conference

Conference3rd IEEE International Conference on Collaboration and Internet Computing, CIC 2017
國家United States
城市San Jose
期間15/10/1717/10/17

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