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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Angular Contour Parameterization for Signature Identification
verfasst von : Juan Carlos Briceño, Carlos M. Travieso, Miguel A. Ferrer, Jesús B. Alonso, Francisco Vargas
Erschienen in: Computer Aided Systems Theory - EUROCAST 2009
Verlag: Springer Berlin Heidelberg
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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.