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