FIELD: information technologies.
SUBSTANCE: invention refers to image recognition, specifically to automatic analysis of handwriting specimen stored in digital form. Quantitative estimation of handwriting specimen similarity is carried out by evaluation of quantitative measure of proximity of vector templates of compared specimens. Formation of every vector template includes making of each handwriting specimen in digital form, separation of grapheme set and processing of this set to produce set of vector descriptions of graphemes thereafter transformed in vector template. Thus graphemes are rated by position and orientation using estimation of line inclination in the initial handwriting specimen; and fixed number of grapheme points and some its metric characteristics are used at the stage of grapheme transformation to vector. Thus using representative learning sample of handwriting specimen description vectors the operator of handwriting specimen description vector reduction to major constituent is found that enables to use vectors of smaller dimensions for analysis and thereby essentially simplify practical implementation of method.
EFFECT: invention allows for simple and reliable comparison of handwriting specimen and for identity verification and personal identification by handwriting.
18 cl, 2 dwg
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Authors
Dates
2008-12-10—Published
2006-09-21—Filed