Signature Classification using Optimum Contour
نویسندگان
چکیده
An offline handwritten signature classification approach is presented. The signature is parameterized using the radius values for contour points in the polar coordinates space. In order to determine the optimum outline for the classification task, nearest and faraway points were took into account. HMM and SVMLight model are analyzed in this work. Selecting faraway points offers better results, and using SVMLight model with polynomial kernel presents the best accuracy values obtained (99,02%). Key-Words: Automatic signature Classification, Hidden Markov Model, Support Vector Machine.
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