MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202621072997 A) filed by Prashant Sheshrao Titare; Mr. Hiraman Jadhav; Kadam Gayatri; Kadam Asmita; and Gawade Artiksha on June 12, 2026, for Talent-Print: Ai-Based Fingerprint Learning And Personality Profiling.
Inventors include Prashant Sheshrao Titare; Mr. Hiraman Jadhav; Kadam Gayatri; Kadam Asmita; and Gawade Artiksha.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: Fingerprint-based biometric traits have been used for identifying and verifying people because they're unique and lasting. Recently, researchers started looking at fingerprints not just as ID tools, but as clues to behavioral and psychological traits. The distinct ridge patterns, minutiae points, and texture variations in a fingerprint are thought to relate genetically and developmentally to certain personality characteristics. This project suggests a method for predicting personality traits by analyzing fingerprints alongside supervised machine learning models. The process includes gathering fingerprint images, doing preprocessing tasks like noise reduction, ridge enhancement, and segmentation, and pulling out significant features such as ridge density, ridge count, minutiae types, and orientation field stats. These traits are then linked to the Big Five personality factors: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. For training and prediction, methods like Support Vector Machine (SVM), Random Forest, and shallow Neural Networks are used to investigate how fingerprint features relate to personality labels collected via psychological surveys. The system also checks performance measures like accuracy, precision, recall, and F1-score to ensure the model’s effectiveness.
Disclaimer: Curated by HT Syndication.
