Quality measures for online handwritten signatures

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter tackles the problem of quality of online signature samples. Several works in the literature point out signature complexity and signature stability as main quality criteria for this behavioral biometric modality. The drawback of these works is the measurement of such criteria separately. In this study, we propose to analyze such criteria with a different unifying view, in terms of entropy-based measures. We consider signature complexity as the intrinsic disorder of a signature instance and variability as the intra-class disorder of a set of genuine signatures. We introduce a novel statistical measure of complexity for signature samples and analyze it relatively to Personal Entropy that we proposed in former works. We study the power of both measures for an automatic writer categorization on several databases. We show that such categories retrieve separately on one hand degraded data and on the other hand good quality signatures. Finally, the degradation of signatures due to mobile acquisition conditions is quantified by our entropy-based measures.

Original languageEnglish
Title of host publicationSignal and Image Processing for Biometrics
PublisherSpringer Verlag
Pages255-283
Number of pages29
ISBN (Print)9783642540790
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Publication series

NameLecture Notes in Electrical Engineering
Volume292
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Keywords

  • Entropy
  • Hidden Markov Models
  • Hierarchical clustering
  • Online signature verification
  • Signature complexity
  • Signature variability
  • Writer categories

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