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This paper presents a set of geometric signature features for offline automatic signature verification based on the description of the signature envelope and the interior stroke distribution in polar and Cartesian coordinates. The features have been calculated using 16 bits fixed-point arithmetic and tested with different classifiers, such as hidden Markov models, support vector machines, and Euclidean distance classifier. The experiments have shown promising results in the task of discriminating random and simple forgeries.
Automatic Signature Verification (ASV), Hidden Markov Models (HMM), Support Vector Machines (SVM), fixed-point arithmetic.

M. A. Ferrer, J. B. Alonso and C. M. Travieso, "Offline Geometric Parameters for Automatic Signature Verification Using Fixed-Point Arithmetic," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 27, no. , pp. 993-997, 2005.
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