DocumentCode :
3490535
Title :
ICDAR 2013 Competitions on Signature Verification and Writer Identification for On- and Offline Skilled Forgeries (SigWiComp 2013)
Author :
Malik, Muhammad Imran ; Liwicki, Marcus ; Alewijnse, Linda ; Ohyama, Wataru ; Blumenstein, Michael ; Found, Bryan
Author_Institution :
German Res. Center for Artificial Intell. (DFKI GmbH), Kaiserslautern, Germany
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
1477
Lastpage :
1483
Abstract :
This paper presents the results of the ICDAR2013 competitions on signature verification and writer identification for on- and offline 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 where training and evaluation data (in Dutch and Japanese) were collected and provided by FHEs and PR-researchers. Four tasks were defined where the systems had to perform Dutch offline signature verification, Japanese offline signature verification, Japanese online signature verification, and Dutch writer identification. The participants of the signatures modality were motivated to report their results in Likelihood Ratios (LR). This has made the systems even more interesting for application in forensic casework. For evaluation of signatures modality, we used both the traditional Equal Error Rate (EER) and forensically substantial Cost of Log Likelihood Ratios (Ĉllr). The system having the smallest value of the Minimum Cost of Log Likelihood Ratio (Ĉllrmin) is declared winner. For evaluation of the handwritten text modality, we used the precision and accuracy measures and winners are announced on the basis of best F-measure value.
Keywords :
handwriting recognition; natural language processing; Dutch offline signature verification; Dutch writer identification; EER; F-measure value; FHE; ICDAR 2013 competitions; Japanese offline signature verification; Japanese online signature verification; LR; PR researchers; SigWiComp 2013; accuracy measures; equal error rate; forensic handwriting examiners; handwritten text modality; minimum cost of log likelihood ratio; offline skilled forgery; online skilled forgery; precision measures; Educational institutions; Feature extraction; Forensics; Forgery; Image edge detection; Training; Writing; Forensic; Signature; Verification; handwriting; identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
ISSN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2013.220
Filename :
6628858
Link To Document :
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