Offline Signature Verification through Probabilistic Neural Network
Files
Date issued
2010
Journal Title
Journal ISSN
Volume Title
Publisher
Václav Skala - UNION Agency
Abstract
In this paper, we show the positive potential of verifying the offline handwritten signatures through discrete
Radon transform (DRT), principle component analysis (PCA) and probabilistic neural network (PNN).
Satisfactory results are obtained with 1.51%, 3.23%, and 13.07% equal error rate (EER) for random, casual, and
skilled forgeries respectively on our independent database.
Description
Subject(s)
offline verifikace podpisu, diskrétní Radonova transformace, analýza hlavních komponent, pravděpodobnostní neuronové sítě
Citation
WSCG 2010: Communication Papers Proceedings: 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, p. 31-38.