Please use this identifier to cite or link to this item:
Title: Grid-based feature distributions for off-line signature verification
Authors: Τσέλιος, Κωνσταντίνος
Ζώης, Ηλίας Ν.
Σιώρης, Ηλίας
Νασιόπουλος, Αθανάσιος Α.
Οικονόμου, Γεώργιος
Item type: Journal article
Keywords: Image classification;Handwriting recognition;Ταξινόμηση εικόνων;Αναγνώριση χειρογράφου
Subjects: Electrical engineering
Ηλεκτρολογική μηχανική
Issue Date: 9-Jan-2015
Publisher: The Institution of Engineering and Technology
Abstract: In this work, a feature extraction method is presented for handwritten signature verification. The proposed algorithm models the handwritten elements of a signature trace by probabilistically counting the distribution of fixed two- and three-step pixel paths, conditioned that they are confined within predetermined Chebyshev distances of two and three, respectively. This representation correlates the pixel transitions along the signature trace, with the writing style of an individual. Various partitions of the signature image into a group of sub-images were applied in order to define the overall dimensionality of the feature. In order to evaluate the classification efficiency of the introduced method, a number of verification strategies are implemented by making use of two internationally accepted and one domestic datasets. In all schemes, similarity scores and hard margin support vector machines (SVMs) are combined or evaluated as separate entities. Additionally, zoning the extracted feature vector into combinations of tetrads and heptads, which in turn are fed into the afore-mentioned classification schemes, is exploited. Results, derived from random or simple imitations as well as simulated (skilled) forgery indicate that the proposed method achieves noticeably low equal error rates and it is expected to provide a powerful discriminative representation of the handwritten signature.
Language: English
Citation: Tselios, K., Zois, E., Siores, E., Nassiopoulos, A. and Economou G. (March 2012). Grid-based feature distributions for off-line signature verification. IET Biometrics. 1(1). pp. 72-81. The Institution of Engineering and Technology.
Journal: IET Biometrics
Type of Journal: With a review process (peer review)
Access scheme: Embargo
License: Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες
Appears in Collections:Δημοσιεύσεις

Files in This Item:
File Description SizeFormat 
  Restricted Access
353.27 kBAdobe PDFView/Open Request a copy

This item is licensed under a Creative Commons License Creative Commons