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Overview: This book presents a novel method of multimodal biometric fusion using a random selection of biometrics, which covers a new method of feature extraction, a new framework of sensor-level and feature-level fusion. Most of the biometric systems presently use unimodal systems, which have several limitations. Multimodal systems can increase the matching accuracy of a recognition system. This monograph shows how the problems of unimodal systems can be dealt with efficiently, and focuses on multimodal biometric identification and sensor-level, feature-level fusion. It discusses fusion in biometric systems to improve performance. Biometric systems use behavioural or physical characteristics to identify individuals. The fingerprint, face, iris, retina, palmprint, speech pattern, signature, gait, and many other characteristics are most often utilised in biometric systems. The two main uses of biometric systems are authentication and identification. A biometric system has various benefits over conventional tech- niques. Biometric characteristics are not lost or forgotten, unlike tokens and passwords. Biometric characteristics are difficult to duplicate, share, transfer, or steal. A biometric system functions as a pattern recognition system by collecting biometric data from each user, extracting a feature set from the collected data, and comparing the feature set with a template that has been stored in the database.
Genre: Non-Fiction > Tech & Devices
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