A Deep Learning Based Analysis of the Big Five Personality Traits from Handwriting Samples Using Image Processing

• Main Authors: Ahmed Elngar, Nikita Jain, Divyanshu Sharma, Himani Negi, Anuj Trehan, Akash Srivastava
• Format: Article
• Language: fas
• Published: University of Tehran 2020-12-01
• Series: Journal of Information Technology Management
• Subjects: computer vision; convolutional neural networks; artificial neural networks; machine learning; big five personality traits; handwriting; graphology
• Online Access: https://jitm.ut.ac.ir/article_78884_2959805560be5b0bf7a105aad7477728.pdf
• ISSN: 2008-5893; 2423-5059

Handwriting Analysis has been used for a very long time to analyze an individual’s suitability for a job, and is in recent times, gaining popularity as a valid means of a person’s evaluation. Extensive Research has been done in the field of determining the Personality Traits of a person through handwriting. We intend to analyze an individual’s personality by breaking it down into the Big Five Personality Traits using their handwriting samples. We present a dataset that links personality traits to the handwriting features. We then propose our algorithm - consisting of one ANN based model and PersonaNet, a CNN based model. The paper evaluates our algorithm’s performance with baseline machine learning models on our dataset. Testing our novel architecture on this dataset, we compare our algorithm based on various metrics, and show that our novel algorithm performs better than the baseline Machine Learning models.