Biometric Identification System Using Hand Dorsal Related Trait

Abstract

In light of the rapid technological development, the biometric system has become a prominent place for many vital applications due to the increasing need for effective and secure means of verifying the identity of users. In this thesis, a dorsal hand recognition system was proposed that is based on identifying biometrics capable of distinguishing between individuals depending on the university of Hong Kong campus. Therefore, we used a deep learning program based on the (CNN) algorithm for classification accuracy, then the matching technique using (SVM). Collects and analyzes data based on the well-known database in this field to test the effectiveness of the system. This study aims to enhance the security and confidence of the biometric identification system through advanced and modern technologies.