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ICPR
2000
IEEE

Off-Line Skilled Forgery Detection Using Stroke and Sub-Stroke Properties

9 years 7 months ago
Off-Line Skilled Forgery Detection Using Stroke and Sub-Stroke Properties
Research has been active in thefield offorgeiy detection, but relatively little work has been done on the detection of skilled forgeries. In thispaper, we present an algorithmfor detecting skilledforgeries based on a local correspondence between a questioned signature and a model obtained a priori. Writer-dependentproperties are measured at the substroke level and a cost function is trainedfor each writer. Whena candidate signature ispresented, the samefeatures are extracted and matched against the model. Wepresent a description of thefeatures and experimental results.
Jinhong Katherine Guo, David S. Doermann, Azriel R
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors Jinhong Katherine Guo, David S. Doermann, Azriel Rosenfeld
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