標題: | Source Identification for Printed Documents |
作者: | Tsai, Min-Jen Yuadi, Imam Yin, Jin-Sheng Tao, Yu-Han 資訊管理與財務金融系 註:原資管所+財金所 Department of Information Management and Finance |
關鍵字: | Forensics;GLCM;Discrete Wavelet Transform (DWT);Support Vector Machines (SVM);Spatial Filter;Wiener Filter;Gabor Filter;Haralick Filter;Fractal Filter |
公開日期: | 1-一月-2017 |
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. |
URI: | http://dx.doi.org/10.1109/CIC.2017.00019 http://hdl.handle.net/11536/147152 |
DOI: | 10.1109/CIC.2017.00019 |
期刊: | 2017 IEEE 3RD INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING (CIC) |
起始頁: | 54 |
結束頁: | 58 |
顯示於類別: | 會議論文 |