Personality Type Analysis through Handwriting Characteristics Mapping using Invariant Moment Descriptors

Abstract

Handwriting patterns are unique to each individual and can offer valuable insights into their mental health conditions, personality traits, behavioral tendencies, mindsets, and more. To effectively analyze someone's personality or solve a problem using their handwriting, it is crucial to employ suitable descriptors that accurately represent the essential information it contains. Therefore, this study aims to explore the application of invariant moments as descriptors to map personality types using the psychological technique of enneagrams in conjunction with handwriting patterns. The main procedures in this research involve pre-processing, texture-based feature extraction utilizing seven invariant moment values, and applying the chi-square similarity measure. Through testing with 49 handwriting samples and 120 reference data points, it was discovered that 42 writings were successfully and accurately mapped to their corresponding personalities, achieving an impressive accuracy rate of 85.7%. This research also reaffirms the validity of personality analysis through a system that utilizes graphological techniques, as demonstrated by a 4.1% increase in accuracy through the inclusion of invariant moment descriptors when compared to psychologist analysis.