Abstract:
"Personality identification through handwriting analysis (Graphology) plays a vital role in
various fields like employee recruitment, counselling, personality development etc. With
the expansion of usages in Graphology, there were problems like less availability of
graphologists, high hiring cost and time consuming. Therefore this research is focused on
providing mobile application solution for predicting the most possible Big-Five personality
group among the 5 groups which are included in Big-Five personality taxonomy by
analyzing handwriting sample using various image-processing techniques and extracts 11
handwriting features. An Ensemble learning approach is used for creating the model.
Trained model for multi-class classification predicts the most possible Big-Five personality
group according to the correlation between handwriting features and Big-Five personality
groups in published research papers."
