In this paper, we analyse the variability of handwritings. The aim is to determine what sort of observations gives a first degree of handwriting characterization before initiating a text recognition process. In the case of handwriting consisting of few words, such literal amounts on cheques, this first degree of characterization can be obtained for each word, independent of signification, by extracting the measures of some pertinent observations. Outcomes of this characterization are, to a certain extent, a distinction between significants which characterise the author and signification which is the semantic aspect. Based on an analysis of 980 different handwritten amounts, it is shown that these measures define a variability space of non-uniform density. A fuzzy partition of the set of 3788 words of the database is proposed which allows to regroup handwriting styles into a small number of specific families.
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