• DocumentCode
    3695278
  • Title

    ICDAR2015 competition on signature verification and writer identification for on- and off-line skilled forgeries (SigWIcomp2015)

  • Author

    Muhammad Imran Malik;Sheraz Ahmed;Angelo Marcelli;Umapada Pal;Michael Blumenstein;Linda Alewijns;Marcus Liwicki

  • Author_Institution
    German Research Center for AI (DFKI GmbH), Kaisersautern, Germany
  • fYear
    2015
  • Firstpage
    1186
  • Lastpage
    1190
  • Abstract
    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 (Ĉllr) in the case of signatures, and the F-measure in the case of handwritten text.
  • Keywords
    "Training","Testing","Correlation","Lead"
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2015 13th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICDAR.2015.7333948
  • Filename
    7333948