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Exploring New Handwriting Parameters for Writer Identification
Abstract
The automatic processing of handwriting samples is part of the computational biometric. It applies qualitative and quantitative techniques by means of capturing, visualizing, and analyzing handwriting. The main applications are writer identification and text understanding. Two significantly different situations appear: online and offline data capturing. In the former, the samples are obtained in a dedicated framework, where the writing instrument and the surface have several sensors. In the latter, the unique information available comes from the residues left on paper. This chapter deals with the second situation. Width, grey value, direction, and other parameters of the residual manuscript text are influenced by the psychomotor characteristics of the writer. Some of these personal parameters may be estimated from the observable properties of the written text.
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