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[null,"1.","Record Nr.",null,"UNINA9910135213103321"]
[null,null,"Titolo",null,"2015 13th International Conference on Document Analysis and Recognition (ICDAR) / / Institute of Electrical and Electronics Engineers"]
[null,null,"Pubbl/distr/stampa",null,"Piscataway, N.J. : , : Institute of Electrical and Electronics Engineers, , 2015"]
[null,null,"ISBN",null,"1-4799-1805-9"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Disciplina",null,"651.5"]
[null,null,"Soggetti",null,"Document imaging systems"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","This paper presents the results of the ICDAR 2015 competition on signature verification and writer identification for on- and off-line skilled forgeries jointly organized by PR researchers and Forensic Handwriting Examiners (FHEs). The aim is to bridge the gap between recent technological developments and forensic casework. Two modalities (signatures and handwritten text) are considered and training and evaluation data are collected and provided by FHEs and PR researchers. Four tasks are defined for four different languages; Bengali off-line signature verification, Italian off-line signature verification, German on-line signature verification, and English handwritten text based writer identification. In total, 40 systems have participated in this competition. The participants of the signatures modality were motivated to report their results in Likelihood Ratios (LRs). This has made the systems even more interesting for application in forensic casework. For evaluating the performance of the systems, we have used the forensically substantial Cost of Log Likelihood Ratios (ɤllr) in the case of signatures, and the F-measure in the case of handwritten text."]