SERIAL MULTIMODAL BIOMETRIC AUTHENTICATION FOR SECURITY

Computer Engineering

In early years monomodel biometric were used. To overcome problems with monomodel biometric like noisy data, error etc. multimodal biometric systems were proposed. In this we are going to use serial fusion biometric mode and semi supervised learning. Face recognition from image or video is a popular topic in biometrics research. Many public places usually have surveillance cameras for video capture and these cameras have their significant value for security purpose. It is widely acknowledged that the face recognition have played an important role in surveillance system as it does not need the object cooperation. The actual advantages of face based identification over other biometrics are uniqueness and acceptance. As human face is a dynamic object having high degree of variability in its appearance, that makes face detection a difficult problem in computer vision. In this field, accuracy and speed of identification is a main issue. Biometrics is a technology which identifies a person based on his physiology or behavioural characteristics. Fingerprint identification and recognition is a biometrics method that has been widely used in various applications because of its reliability and accuracy in the process of recognizing and verifying a persons identity. The main purpose of this framework is to develop a fingerprint identification and recognition system. The system consists of two main parts face detection and finger print recognition. Fingerprint images are acquired and stored in the database in the image acquisition stage. These images are then enhanced in the image processing and we use this framework in IT server room for authentication purpose.

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