Handwriting Style based Personality Classification using Cognitive Learning

Abstract

Graphology uses the handwriting styles of individuals to assess their personality. There is an increasing research interest in the personality assessment of individuals in terms of the Big Five personality model.  Questionnaire responses, visual cues of individuals, etc. are being mapped to Big Five personality traits. In this work, three handwriting characteristics are derived from handwritten documents: slant, connectedness between letters, and zonal presence. A cognitive learning classifier is developed with these characteristics to classify the individual's big five personalities. The proposed solution's efficacy is evaluated using a variety of handwritten materials.