完整後設資料紀錄
DC 欄位語言
dc.contributor.authorTsai, Min-Jenen_US
dc.contributor.authorYuadi, Imamen_US
dc.date.accessioned2017-04-21T06:50:14Z-
dc.date.available2017-04-21T06:50:14Z-
dc.date.issued2016en_US
dc.identifier.isbn978-1-4673-9961-6en_US
dc.identifier.issn1522-4880en_US
dc.identifier.urihttp://hdl.handle.net/11536/134330-
dc.description.abstractThe 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.en_US
dc.language.isoen_USen_US
dc.subjectMicroscopic Imagesen_US
dc.subjectForensicsen_US
dc.subjectLocal Binary Pattern (LBP)en_US
dc.subjectprinted documenten_US
dc.titlePrinted Source Identification by Microscopic Imagesen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)en_US
dc.citation.spage3927en_US
dc.citation.epage3931en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000390782003186en_US
dc.citation.woscount0en_US
顯示於類別:會議論文