ICDAR2015 Competition on Signature Verification and Writer Identification for On- and Off-line Skilled Forgeries (SigWIcomp2015)

2017-12-04 (v. 1)

Contact author

Muhammad Imran Malik

National University of Sciences and Technology, Islamabad, Pakistan

iimranmalik@gmail.com

00925190852190

92-51- 8317363

You can cite this dataset as: Muhammad Imran Malik, ICDAR2015 Competition on Signature Verification and Writer Identification for On- and Off-line Skilled Forgeries (SigWIcomp2015) ,1,ID:SigWIcomp2015_1,URL:http://tc11.cvc.uab.es/datasets/SigWIcomp2015_1

Dataset Information

Keywords

Description

Keywords

Forensic analysis, signatures, handwriting, off-line, on-line, verification, identification, evaluation, likelihood ratios

Description

 

Objectives

The objective of this competition is to allow researchers and practitioners from academia and industries to compare their performance in signature verification on new unpublished forensic-like datasets (Bengali, German, and Italian). Skilled forgeries and genuine signatures were collected while writing on a paper in some cases it was attached to a digitizing tablet. The collected signature data are available in an offline format and some signatures are also available in online format. Participants can choose to compete on the online data or offline data only, or can choose to combine both data formats.

Similar to the last ICDAR competition, our aim is to compare different signature verification algorithms systematically for the forensic community, with the objective to establish a benchmark on the performance of such methods (providing new unpublished forensic-like datasets with authentic and skilled forgeries in both on- and offline format).

Background

The Forensic Handwriting Examiner (FHE) weighs the likelihood of the observations given (at least) two hypotheses:

  • H1: The questioned signature is an authentic signature of the reference writer;
  • H2: The questioned signature is written by a writer other than the reference writer;

The interpretation of the observed similarities/differences in signature analysis is not as straightforward as in other forensic disciplines such as DNA or fingerprint evidence, because signatures are a product of a behavioral process that can be manipulated by the reference writer himself, or by another person than the reference writer. In this competition, we ask to produce two probability scores: The probability of observing the evidence (e.g. a certain similarity score) given H1 is true, and the probability of observing the evidence given H2 is true. In this competition only such cases of H2 exist, where the forger is not the reference writer. This continues the last successful competitions on ICDAR 2009, 2011, and 2013.

 

 

 

Technical Details

General information

The password for opening the data files is gien below:

“IherebyaccepttheSigWIcomp2015disclaimer” (without quotes).

For technical deatils refer to the SigWIcomp2015 paper, attached here as well. 

FileTypeSizeDownloadsDescription
SigWIcomp2015-Data.zipdata(4 MB)24Training and test sets of Bengali and Italian Signatures data (off-line), and training and test set of German signature data (on-line).
2015-SigWIcomp.pdfarticle(182 KB)21Competition report

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ICDAR2015 Competition on Signature Verification and Writer Identification for On- and Off-line Skilled Forgeries