The approach is based on a combination of classical geometric arithmetic evaluation and fuzzy control designs. For determination of the base line angle two methodologies are explored: the geometric-features based segmentation method and a method based on biologically inspired generation theories or the low pass filtering method. We utilize the geometric features evaluation for the baseline extraction since it proves more robust with respect to the variations of the handwriting in an off-line environment.

For determination of the slant type a fuzzy technique is adopted to determine the contributions of the slant-type angle to each of the five variations of the slant-type categories. The uncertainties in the system model are expressed by fuzzy-valued model parameters with their membership functions derived from experimental data. In total five variations of slant type are considered. These include extreme left, controlled left, vertical, controlled right and extreme right.

Fifteen personality traits PT1 - PT15 were identified and sets of rules formulation were created, (e.g., If Input1 is "level" and "Input2" is "Controlled Left" then Output is PTx.)

The proposed approach takes advantage of two differing methodologies that have clear outputs to evaluate two attributes of handwriting. The outputs are utilized to determine a personality trait. The system can be further enhanced by including more parameters such as size of letters, spacing between letters and other attributes of handwriting as part of the inputs for trait determination.

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