A Comprehensive Study on the Role of Machine Learning in Hybrid Biometric Recognition

There is a potential issue with unimodal biometric recognition systems. If the system is only able to use a single type of biometric, such as fingerprints, there is a risk that the system could be fooled by a fake fingerprint. As a result, this research study investigates how a hybrid biometric recognition system (HBRS) can overcome the problem with biometrics that rely on a single attribute for recognition. A HBRS is a system that uses more than one type of biometric recognition technology. Machine learning (ML) is used in biometric recognition to improve the accuracy of the recognition system. Therefore, this research study explore the role of machine learning in this identification process, as well as several machine learning algorithms that aid in the construction of HBRS systems, to see which methods provide the best accuracy.