The personality and characteristics study of Farsi handwriting using decision tree

Graphology is a technical knowledge that presented a person, character or mood. In this research, by obtaining handwriting and personality questionnaire MMPI from different people, we formed a database. A decision tree was exploited as a machine learning tool for grouping extracted features. The proposed system can predict individual characteristic of the writer with scanning the handwriting sample. The samples included 140 subjects in two different groups. These groups include 70 clients of Semnan prison and 70 students of Semnan University of Applied Sciences. In order to obtain the handwriting, a neutral and smooth text was chosen and wanted the subjects to write in a non-line of A4 paper. A decision tree is used for a final recognition. To verify the recognition of the decision tree, the output of MMPI questionnaire was used that yielded promising result. Results of extracted features accuracy obtained by the proposed method showed %87 to %94 match the observations. %69 personality recognition accuracy (result of the decision tree) achieved compared with the results obtained personality MMPI questionnaire.