Title :
Printing Technique Classification for Document Counterfeit Detection
Author :
Lampert, Christoph H. ; Mei, Lin ; Breuel, Thomas M.
Author_Institution :
German Res. Center for Artificial Intelligence, Image Understanding & Pattern Recognition Lab., Kaiserslautern
Abstract :
The detection of counterfeit in printed documents is currently based mainly on built-in security features or on human expertise. We propose a classification system that supports non-expert users to distinguish original documents from PC-made forgeries by analyzing the printing technique used. Each letter in a document is classified using a support vector machine that has been trained to distinguish laser from inkjet printouts. A color-coded visualization helps the user to interpret the per-letter classification results
Keywords :
document handling; fraud; ink jet printers; pattern classification; printing; PC-made forgeries; color-coded visualization; document counterfeit detection; inkjet printouts; laser printouts; letter classification; per-letter classification results; printing technique classification; support vector machine; Artificial intelligence; Counterfeiting; Data mining; Forgery; Humans; Ink; Laser transitions; Printing; Security; Spatial databases;
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
DOI :
10.1109/ICCIAS.2006.294214
