A Novel Idea for Age Invariant Face Recognition

Biometric identification is the technique of automatically identifying or verifying an individual by a physical characteristic or personal trait. The term “automatically” means the biometric identification system must identify or verify a human characteristic or trait quickly with little or no intervention from the user. A face recognition system is non-invasive means it allow user to be identified by simply walking past a camera. Human beings often recognize one another by unique facial characteristics. Automatic facial recognition also uses certain facial characteristics that are unique in nature. Facial recognition is the most successful form of human surveillance. The basic idea of this work focuses on the updation of corpus (database) by using a method based on feature extraction which is combined with minimization algorithm for searching process. This approach may be applied to other databases in which the data items varies with time such as human signature and other behavioural activities. The proposed idea first extracts features from the face images. These extracted features are stored in database during training period. Later on this database is used for identification. At the time of identification certain fitness function is calculated, if the value of fitness function decreases below a threshold value then the database is updated with features extracted from new image that is being identified. As in proposed idea the corpus is updated during recognition phase, it is expected to gives high acceptance rate as compared to static matching of face images. The application of this project range from static matching of controlled format photographs such as passports, credit cards, photo ID’s, drivers licenses, and mug shots to real time matching of surveillance video images.