DocumentCode :
3695157
Title :
A Conditional Random Field model for font forgery detection
Author :
Romain Bertrand;Oriol Ramos Terrades;Petra Gomez-Kramer;Patrick Franco;Jean-Marc Ogier
Author_Institution :
Laboratory L3i, University of La Rochelle, Avenue Michel Cré
fYear :
2015
Firstpage :
576
Lastpage :
580
Abstract :
Nowadays, document forgery is becoming a real issue. A large amount of documents that contain critical information as payment slips, invoices or contracts, are constantly subject to fraudster manipulation because of the lack of security regarding this kind of document. Previously, a system to detect fraudulent documents based on its intrinsic features has been presented. It was especially designed to retrieve copy-move forgery and imperfection due to fraudster manipulation. However, when a set of characters is not present in the original document, copy-move forgery is not feasible. Hence, the fraudster will use a text toolbox to add or modify information in the document by imitating the font or he will cut and paste characters from another document where the font properties are similar. This often results in font type errors. Thus, a clue to detect document forgery consists of finding characters, words or sentences in a document with font properties different from their surroundings. To this end, we present in this paper an automatic forgery detection method based on document font features. Using the Conditional Random Field a measurement of probability that a character belongs to a specific font is made by comparing the character font features to a knowledge database. Then, the character is classified as a genuine or a fake one by comparing its probability to belong to a certain font type with those of the neighboring characters.
Keywords :
"Forgery","Printers"
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2015 13th International Conference on
Type :
conf
DOI :
10.1109/ICDAR.2015.7333827
Filename :
7333827
Link To Document :
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