Off-line signature verification using structural feature correspondence

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

52 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)2467-2477
Journal / PublicationPattern Recognition
Volume35
Issue number11
Publication statusPublished - Nov 2002
Externally publishedYes

Abstract

This paper presents an off-line signature verification method using a model-based approach. In this method, statistical models are constructed for both pixel distribution and structural layout description. In addition to simple geometric handwriting features, it is proposed to use the directional frontier feature as a structural descriptor of the signature. The statistical verification algorithm based on the geometric handwriting feature is used to accept signatures which closely resemble the reference samples, and to reject random and less skilled forgeries. For the questionable signatures for which the pixel feature judgement is inconclusive, the structural feature verification algorithm is invoked. This algorithm compares the detailed structural correlation between the input and reference signatures in an attempt to detect skilled forgeries. The effectiveness of the approach is evaluated on an experimental signature database. © 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

Research Area(s)

  • Directional frontier, Relaxation matching, Signature verification, Structural model

Citation Format(s)

Off-line signature verification using structural feature correspondence. / Huang, Kai; Yan, Hong.
In: Pattern Recognition, Vol. 35, No. 11, 11.2002, p. 2467-2477.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review