Exploring New Handwriting Parameters for Writer Identification

Exploring New Handwriting Parameters for Writer Identification

DOI: 10.4018/978-1-5225-7368-5.ch057
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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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The information recovered off-line from the static residues left on the paper is called pseudo-dynamic. It is clearly different from the actual dynamic information captured on-line during the writing activity. There are many contributions proposing different pseudo-dynamic characteristics, most of them oriented to signature authentication, which is a sub-problem of identification of the author of free text. Some of them are summarized in the next paragraphs.

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