This research project explores the relationship between handwriting patterns and personality traits using Deep Learning. Handwriting samples have been collected and analyzed from multiple individuals, focusing on how they write different alphabets to uncover underlying personality traits. The project involved extensive image processing techniques, including noise reduction, binarization, and feature extraction, to enhance the quality of handwritten samples. Leveraging Convolutional Neural Networks (CNNs) and Transfer Learning, I trained models to classify personality traits based on handwriting characteristics.
By combining graphology with machine learning, this study demonstrates how AI can be used for behavioral analysis and psychological profiling, offering potential applications in forensics, recruitment, and psychological assessments.