Analysis and Recognition of Handwriting Patterns for Personality Trait Prediction Using Unsupervised Machine Learning Approach

Abstract

The study of the link between handwriting and personality is known as handwriting analysis. It is a specific manner of using handwriting to convey one’s cognitive process. That’s why it’s also known as “brain writing”. Handwriting, like a person’s fingerprint, is a unique trait that cannot be duplicated by two distinct people. It also aids us in determining a person’s emotional state. Handwriting recognition is usually done in a traditional manner, in which a professional handwriting expert examines a person’s handwriting samples for various personality features, which takes a lot of time and effort. As a result, the focus of this study is on developing an automated system that can predict personality characteristics utilizing the machine learning algorithm KNN to identify a certain individual based on their handwriting sample. In today’s modern society, predicting personality traits using face, voice, handwriting, and other techniques is becoming increasingly essential. To develop this approach, we look at a document’s many features such as letter size, word spacing, and slant of words, pen pressure, and baseline, and so on to anticipate the writer’s personality.