Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46173
Title: Handwritten signatures recognizer by its envelope and strokes layout using HMM's
Authors: Sánchez, J. A.
Travieso, C. M. 
Alonso, I. G. 
Ferrer, M. A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Handwriting recognition
Hidden Markov models
Automatic speech recognition
Karhunen-Loeve transforms
Fast Fourier transforms
Issue Date: 2001
Journal: IEEE Annual International Carnahan Conference on Security Technology, Proceedings
Conference: 35th Annual International Carnahan Conference on Security Technology 
35th Annual 2001 International Carnahan Conference on Security Technology 
Abstract: A method for the automatic recognition of offline handwritten signatures using both global and local features is described. As global features, we use the envelope of the signature sequenced as polar coordinates; and as local features we use points located inside the envelope that describe the density or distribution of signature strokes. Each feature is processed as a sequence by a hidden Markov Model (HMM) classifier. The results of both classifiers are linearly combined, obtaining a recognition ratio of 95.15% with a database of 60 handwritten signatures.
URI: http://hdl.handle.net/10553/46173
ISBN: 0-7803-6636-0
Source: IEEE Annual International Carnahan Conference on Security Technology, Proceedings, p. 267-271
Appears in Collections:Actas de congresos
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