The Biometric Facial Recognition Process - Term Paper Example

BIOMETRICS Introduction Biometrics refers to the unique personal, physical and measurable characteristics that can be used to identify an individual. The process involves both identification and verification of these traits. The identification process is different from the verification process in that verification involves comparison of the facial feature of a subject with the features of one other face to ascertain whether they match while identification involves comparison with several other faces to determine which of them accurately matches with the subject. There are various kinds of biometrics one of the most common being facial recognition. In facial recognition, the spatial geometry of the facial biometrics is recorded. There are various ways of facial recognition but the common feature for all of them is the fact that they all rely on measurement of the distinguishable facial features (Woodward et al. 3). The biometric facial recognition process The process of facial recognition occurs in five steps. The first step involves capturing the image. The image can either be a scan of a previously captured image or a photograph that has been captured live by the use of a digital video camera. Videos are also possible sources of facial images. The second step involves searching for the location of the face within the image. This process involves using the mouth and two eyes positioned in the shape of an oval. In the third stage, the face is removed from the rest of the image. To do this, various optional methods are available. When the face has been extracted it is now known as a template whose characteristic data is in a reduced form. The fourth stage involves the comparison of the already obtained templates with other pre-recorded faces on a database. The fifth and final stage is a declaration of matches based on the strength of the scores generated from the comparison (Woodward et al. 8) Security of biometric facial recognition Despite the many benefits associated with the use of this technology there are also some risks pertaining to its use. Like any other technology requiring the use of the internet for data transmission, privacy is a major concern. The social media sites are the major areas where privacy of the images generated through this technology may be used inappropriately leading to violation of user’s privacy rights. The biometric data may also reach the wrong people leading to problems such as identity theft or online stalking (Iowa State University 1). Application of biometric facial recognition Access control Facial recognition has been used to deny access to unauthorized persons to restricted locations or systems. It can be used to control entry into computer systems in place of a user password whereby the computers are provided with an inbuilt camera with the capability to identify faces. The technology has been used to control access to restricted documents as well as authorization to carry out certain transactions. A good example is the use of face verification in cheque-cashing kiosks. Automatic Teller Machines are also fitted with cameras for the purpose of authentication. Financial institutions such as banks also use this technology for the purpose of access control (Senior and Bolle 108). Identification In combination with human identification and demographics, face recognition has found application in enrollment of applicants whereby it has been used to prevent double or multiple enrolment by use of different identities. It is also used in the process of issuing licenses and other legal documents to avoid the problem of people having multiple identities. Surveillance Video surveillance footages of certain occurrences such as crime have been used as sources of the images which can be analyzed through face recognition to identify individuals involved. Live images of face recognition surveillance have been used to identify interesting persons within a group (Senior and Bolle 109). Pervasive computing The passive nature of face recognition can be used with most computing devices to enable them to sense and identify users of such devices or even other people within their close proximity over a user interface. In addition there are devices with user personalization capabilities on the basis of identification through an in-build camera. This capability of face recognition can make it possible for such technological advances as phone call redirection through system identification, automatic information about visitor in a certain area or generation of labeled transcripts of conference undertakings via video conference (Senior and Bolle 110). Is biometric facial recognition common? Biometric facial recognition is the most common form of biometric recognition. It is more preferable due to the many advantages it has over other methods. It is less intrusive as it permits for taking of images from a considerable distance without the need for physical contact with the individual. Archived images can be retrieved later for use in identifying a person hence it plays the purpose of deterring crime. Face recognition systems have in recent times found an increasing application rate. The future of biometric facial recognition is quite promising with future advancements of the technology expected to further increase its application (Senior and Bolle 110). False rejection Biometric facial recognition just like any other biometric system is prone to errors which may occur through two ways. The first type of error is the False Accept error characterized by the acceptance of the wrong individual as the legitimate subject. The other error is the False Reject error which manifests by denying a legitimate subject access (Senior and Bolle 104). A good example of false rejection occurs with banks whereby biometric facial recognition is used as a way to prevent fraud. Customers may be false rejected by the system and denied access when they are truly legitimate. This kind of an error has led to many banks becoming reluctant to use the technology in order to prevent the risk of losing important customers. Customers find the burden of having to go through extra security measurers uncomfortable given that the law limits their personal liability (Senior and Bolle 109). How to minimize false rejection False rejection is an error that can be minimized by use of algorithms that are robust and providing passive acquisition capabilities coupled with high accuracies and low probabilities of rejection. One algorithm that is capable of minimizing false rejection is the 3-D face recognition. Previously, face recognition was 2-D domain which does not offer reliable accuracy as it is affected by variations of the face from one instant to another. The 3-D face recognition domain is capable of differentiating the geometry of the face to a very high accuracy. With 3-D face recognition, the subject does not have to be positioned at an exact point with respect to the device nor does he/she have to be in direct physical contact with it (Artec 1). 3-D face recognition In 3-D face recognition algorithm, data can be acquired through various methods one of which is stereo acquisition which involves the use of a number of 2-D cameras which are calibrated to capture images from different perspectives simultaneously. These images are then used for the reconstruction of a 3-D platform. A more expensive method of 3D data acquisition is by the use of 3d scanners which capture the 3d image at once. To protect the templates they are stored in form of a biometric encryption which does not permit feasible retrieval of the original data (Zhou 317). Use of biometric face recognition in consumer products Biometrics of face recognition has found application in consumer products. These consumer applications include; protection of residential property whereby face recognition can be used to deny access of strangers to homes by use of biometric locks which are provided with face recognition systems. In retail business, it is possible for the management to determine unauthorized individuals from entering the enterprise especially in establishments where entry is restricted for certain individuals on the basis of age. A good example is the use of biometric face recognition to identify underage customers in a bar. Biometrics of face recognition has also been used by pharmacists to identify customers who are allergic to some drugs from a far. With the rapid worldwide acceptance of the technology, many products have been developed to allow for better engagement of consumers and communication. Biometric face recognition is being used in consumer products such as cosmetics and other goods for household use. Over the years, there has been a great deal of penetration biometric face recognition in the consumer market (FindBiometrics 1). References Artec. Artec Group: Walk through identification. 2013. Web. 11 Oct. 2013. FindBiometrics. Consumer / Residential Biometrics. 2013. Web. 11 Oct. 2013. Iowa State University. Benefit vs. risk of facial recognition technology. 2013. Web. 11 Oct. 2013. Senior, Andrew W. and Bolle, Ruud M. Face Recognition and its Applications. 2013. Web. 11 Oct. 2013. Woodward, John D. Biometrics: A Look at Facial Recognition. 2003. RAND. Pittsburg Zhou, Xuebing et al. Template Protection for 3D Face Recognition. 2010. Web. 11 Oct. 2013. Read More