Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44075
Title: Angular contour parameterization for signature identification
Authors: Briceño, Juan Carlos
Travieso, Carlos M. 
Ferrer, Miguel A. 
Alonso, Jesús B. 
Vargas, Francisco
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Signature identification, Biometric system, Edge parameterization, Handwritten Writing, Document analysis, Classification system Pattern Recognition
Issue Date: 2009
Publisher: 0302-9743
Journal: Lecture Notes in Computer Science 
Conference: 12th International Conference on Computer Aided Systems Theory (EUROCAST 2009) 
12th International Conference on Computer Aided Systems Theory, EUROCAST 2009 
Abstract: This present work presents a parameterization system based on angles from signature edge (2D-shape) for off-line signature identification. We have used three different classifiers, the Nearest Neighbor classifier (K-NN), Neural Networks (NN) and Hidden Markov Models (HMM). Our off-line database has 800 writers with 24 samples per each writer; in total, 19200 images have been used in our experiments. We have got a success rate of 84.64%, applying as classifier Hidden Markov Model, and only used the information from this edge detection method.
URI: http://hdl.handle.net/10553/44075
ISBN: 978-3-642-04771-8
3642047718
ISSN: 0302-9743
DOI: 10.1007/978-3-642-04772-5_47
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 5717 LNCS, p. 358-365
Appears in Collections:Actas de congresos
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