Combining Snakes and Neural Networks for Off-Line Signature Verification - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2006

Combining Snakes and Neural Networks for Off-Line Signature Verification

Abstract

This paper introduces an improved snake algorithm based on the work by Kass et al. Our approach is applied to the off-line signature verification problem where signatures are scanned and then converted into binary images. This way no dynamic information of the signers is available. We also have considered some real conditions for the verification problem when applied to bank check. For example our system uses only one training signature per subject. Involved system parameters are tuned to solve the task in an effective and efficient manner. A two-layer perceptron is build for signature classification and it uses only two signature features (distance and matching factor) provided by the adjusted snake. Finally, a study of the system for a signature database is provided.
Fichier principal
Vignette du fichier
cr1026231491271.pdf (600.49 Ko) Télécharger le fichier
Loading...

Dates and versions

inria-00103939 , version 1 (05-10-2006)

Identifiers

  • HAL Id : inria-00103939 , version 1

Cite

José F. Vélez, Ángel Sánchez, Ana B. Moreno, José L. Esteban. Combining Snakes and Neural Networks for Off-Line Signature Verification. Tenth International Workshop on Frontiers in Handwriting Recognition, Université de Rennes 1, Oct 2006, La Baule (France). ⟨inria-00103939⟩

Collections

IWFHR10
73 View
166 Download

Share

Gmail Facebook Twitter LinkedIn More