ML-Based Personality Detection Using Handwriting Analysis
Prof. Nikhil S. Band1, Ankush R. Lakade2, Purva S. Kale3, Sujit B. Sable4, Rushikesh P. Jadhao5
1Department Of Information Technology, Prof. Ram Meghe Institute Of technology & research, Amravati-444607, Maharashtra, India
2Department Of Information Technology, Prof. Ram Meghe Institute Of technology & research, Amravati-444607, Maharashtra, India
3Department Of Information Technology, Prof. Ram Meghe Institute Of technology & research, Amravati-444607, Maharashtra, India
4Department Of Information Technology, Prof. Ram Meghe Institute Of technology & research, Amravati-444607, Maharashtra, India
5Department Of Information Technology, Prof. Ram Meghe Institute Of technology & research, Amravati-444607, Maharashtra, India
ABSTRACT
Handwriting analysis, or graphology, serves as a significant psychological tool for deciphering human personality through idiosyncratic writing patterns. While these patterns reflect an individual’s cognitive and emotional makeup, traditional methods rely heavily on manual interpretation. This human-centric approach is often hampered by subjectivity, significant time constraints, and inherent inconsistencies between different analysts, limiting its reliability in professional settings.
To address these challenges, this study introduces an automated framework for personality detection leveraging machine learning. The proposed system integrates advanced image processing with a Convolutional Neural Network (CNN) to autonomously extract and analyse critical stylistic features, including slant, word spacing, stroke dynamics, and baseline alignment. By digitizing the feature extraction process, the model classifies personality traits with a level of precision and consistency that surpasses conventional manual techniques.
Deep learning effectively modernizes behavioural analysis, providing a scalable, objective tool for recruitment and psychological profiling. By merging traditional graphology with computational intelligence, this approach offers a robust framework for understanding human behaviour.
Keywords: Handwriting Analysis, Convolutional Neural Networks (CNN), Personality Detection, Machine Learning, Image Processing, Behavioural Analysis.
