Face Recognition System: Different Methods Of Face Recognition
Face recognition system is gaining wide acceptance in security industry
. Companies, firms, hospitals, schools and colleges, defense, and high-profile government offices make use of biometric face recognition appliance daily. It promises hassle-free operation, higher accuracy, and better safety as compared to the conventional security solutions. You need not worry about the security of your premises, if you have a face recognition system installed. You can also combine the biometric face recognition technology with different type of software to carry out specific tasks.
The system uses unique and unalterable facial features to recognize faces. Distance between the two eyes, eyes and nose, shape of cheek bones and other features remain the same throughout their lives. The entire face is measured and analyzed. A typical face recognition system has many face templates stored in its database. Whenever a person approaches the biometric face recognition application, the live face is compared with the faces in the database. Only if the face is recognized, the person is granted access to the premises. Accuracy in face detection depends on the algorithm used by the face recognition system.
Modern face recognition systems use different methods for face detection. Main methods may be given as below:
* Feature analysis: As per the Feature Analysis theory, human beings recognize faces by looking at the individual parts. For example, you may recognize a friend's face better by its certain striking features. This was the first theory of facial recognition; many face recognition system were devised based on this theory. Individual features of the face are used to differentiate between faces.
* Neural network: Face recognition system can also be designed with artificial neural networks. Artificial neural networks can be programmed to solve artificial intelligence problems like face detection. In this method, images are stored in the database. The system is designed and trained to recognize the faces in the database. Neural network biometric face recognition is considered to be better than other methods in terms of accuracy.
* Eigenfaces: Eigenfaces are also known as Principal Components. The live image is discriminated into the face stored in the database of a face recognition system. The input signals or the live face is noisy, i.e. it is influenced by various external factors like lighting conditions, pose, etc. Despite this, there are certain patterns on the face which can be observed in any condition. These specific characteristics are called eigenfaces. Facial recognition can be made through eigenfaces.
* Automatic face processing: This method involves scanning a person's face and matching the image with a database of known faces. Automatic face processing is used to track terrorists, thieves and anti-social elements. Airports, defense and other areas where maximum security is to be maintained, automatic face processing biometric face recognition are used.
Application of face recognition system is increasing day-by-day. Irrespective of the method used, the advanced security solution is emerging as the need of the day! Earlier face recognition systems were seen only in highly sensitive areas like secret government offices. Other than this, they were seen in science fiction movies! Nowadays, you may come across biometric face recognition systems in ordinary places like an office or restaurant. Face recognition system is a reliable security instrument.
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