Title : 
A System Based on Intrinsic Features for Fraudulent Document Detection
         
        
            Author : 
Bertrand, Romain ; Gomez-Kramer, Petra ; Ramos Terrades, Oriol ; Franco, Paulo ; Ogier, Jean-Marc
         
        
            Author_Institution : 
Lab. L3i, Univ. of La Rochelle, La Rochelle, France
         
        
        
        
        
        
            Abstract : 
Paper documents still represent a large amount of information supports used nowadays and may contain critical data. Even though official documents are secured with techniques such as printed patterns or artwork, paper documents suffer from a lack of security. However, the high availability of cheap scanning and printing hardware allows non-experts to easily create fake documents. As the use of a watermarking system added during the document production step is hardly possible, solutions have to be proposed to distinguish a genuine document from a forged one. In this paper, we present an automatic forgery detection method based on document´s intrinsic features at character level. This method is based on the one hand on outlier character detection in a discriminant feature space and on the other hand on the detection of strictly similar characters. Therefore, a feature set is computed for all characters. Then, based on a distance between characters of the same class, the character is classified as a genuine one or a fake one.
         
        
            Keywords : 
document image processing; feature extraction; image classification; object detection; automatic forgery detection method; character classification; document intrinsic features; document production step; feature set; fraudulent document detection; information supports; intrinsic features; paper documents; watermarking system; Feature extraction; Forgery; Noise; Security; Shape; Software; Vectors; document analysis; fake; forgery; fraudulent document; paper document;
         
        
        
        
            Conference_Titel : 
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
         
        
            Conference_Location : 
Washington, DC
         
        
        
        
            DOI : 
10.1109/ICDAR.2013.29