Hybrid Component-Based Face Recognition System

Face recognition system is a fast growing research field because of its potential as an eminent tool for security surveillance, human-computer interaction, identification declaration and other applications. Face recognition techniques can be categorized into 3 categories namely holistic approach, feature-based approach, and hybrid approach. In this paper, a hybrid component-based system is proposed. Linear discriminant analysis (LDA) is used to extract the feature from each component. The outputs from the individual components are then combined to give the final recognition output. Two methods are used to obtain the components, namely the facial landmarks and the sub-images. It was found out that the fusion of the components does improve the recognition rate compared to individual results of each component. From the sub-image method, it can be seen that as the size of the components get smaller, the recognition rate tends increase but not always.