Deep Learning-Based Person Authentication Using Convolutional Neural Architecture Hand Radiographs: A Forensic Approach
B Moniga, D Nandika, PS Monica, Vaidehi Basavakumar Roopa · 2021
Biometric x-rays are a means of testing the physical properties of an individual to check their identity. There are, anatomical attributes, such as eyes or traits of behavior, fingerprints, and a special path to authentication. In this article, the use of a deep neural network with fuzzy clustering is proposed as a new approach for forensic radiography-based human authentication. A complex, convolutional neural architecture is used to derive features of hand x-rays and for the detection of fluid clusters. Our experiment shows that hand x-rays provide biometric data which can be used to recognize the victims. The research reveals that the model proposed here is considerably stronger when compared to previously developed authentication systems with hand X-rays.