|Title:||Handwriting knowledge based on parameterization for writer identification||Authors:||Romero, Carlos F.
Travieso, Carlos M.
Ferrer, Miguel A.
Alonso, Jesús B.
|UNESCO Clasification:||3307 Tecnología electrónica||Issue Date:||2009||Publisher:||1876-1100||Journal:||Lecture Notes in Electrical Engineering||Conference:||European Computing Conference||Abstract:||This present paper has worked out and implemented a set of geometrical characteristics from observation of handwriting. In particular, this work has developed a proportionality index together with other parameters applied to handwritten words, and they have been used for writer identification. That set of characteristics has been tested with our offline handwriting database, which consists of 40 writers with 10 samples per writer. We have got a success rate of 97%, applying a neural network as classifier.||URI:||http://hdl.handle.net/10553/44073||ISBN:||9780387848136||ISSN:||1876-1100||DOI:||10.1007/978-0-387-84814-3_1||Source:||Lecture Notes in Electrical Engineering[ISSN 1876-1100],v. 27 LNEE, p. 3-13|
|Appears in Collections:||Actas de congresos|
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