完整後設資料紀錄
DC 欄位語言
dc.contributor.authorTsai, Min-Jenen_US
dc.contributor.authorYin, Jin-Shenen_US
dc.contributor.authorYuadi, Imamen_US
dc.contributor.authorLiu, Jungen_US
dc.date.accessioned2019-04-02T06:00:09Z-
dc.date.available2019-04-02T06:00:09Z-
dc.date.issued2014-12-01en_US
dc.identifier.issn1380-7501en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s11042-013-1642-2en_US
dc.identifier.urihttp://hdl.handle.net/11536/147815-
dc.description.abstractRecently, digital forensics, which involves the collection and analysis of the origin digital device, has become an important issue. Digital content can play a crucial role in identifying the source device, such as serve as evidence in court. To achieve this goal, we use different texture feature extraction methods such as graylevel co-occurrence matrix (GLCM) and discrete wavelet transform (DWT), to analyze the Chinese printed source in order to find the impact of different output devices. Furthermore, we also explore the optimum feature subset by using feature selection techniques and use support vector machine (SVM) to identify the source model of the documents. The average experimental results attain a 98.64 % identification rate which is significantly superior to the existing known method of GLCM by 1.27 %. The superior testing performance demonstrates that the proposed identification method is very useful for source laser printer identification.en_US
dc.language.isoen_USen_US
dc.subjectDigital image forensicsen_US
dc.subjectGraylevel co-occurrence Matrix (GLCM)en_US
dc.subjectDiscrete Wavelet Transform (DWT)en_US
dc.subjectFeature Selectionen_US
dc.titleDigital forensics of printed source identification for Chinese charactersen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s11042-013-1642-2en_US
dc.identifier.journalMULTIMEDIA TOOLS AND APPLICATIONSen_US
dc.citation.volume73en_US
dc.citation.spage2129en_US
dc.citation.epage2155en_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:000344744200046en_US
dc.citation.woscount9en_US
顯示於類別:期刊論文