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

Volume

1

fYear

2006

fDate

Nov. 2006

Firstpage

639

Lastpage

644

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICCIAS.2006.294214

Filename

4072167