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In this paper a biometric recognition system based on handwritten words is presented. The system relies on a pair of catalogues of strokes that are built unsupervisedly by means of self-organizing maps. One of the catalogues categorizes pen-down strokes (the strokes executed exerting pressure on the writing surface) while the other categorizes pen-up strokes (in-air movements of the hand performed while transitioning from one pen-down stroke to the next). These catalogues allow mapping sequences of strokes into sequences of integers. The latter, much simpler sequences, can be effectively compared by means of dynamic time warping, taking advantage of the neighboring properties exhibited by self-organizing maps. The system yields considerably good results both in identification (95.6% accuracy) and in verification (1.57 % error) when tested with 320 users and one handwritten word.
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