Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UKDiss.com.
Facial recognition is a crucial factor of everyday identification processes: human beings recognize and evaluate each other by means of the face. Whenever driving licences, identity and membership cards are checked or wherever access is controlled by security staff, the identity is verified by looking into somebody’s face. Thus, unlike other biometric features, e.g. the fingerprint or iris recognition, facial recognition is a transparent procedure well-known to human beings. However, especially in the context of the international fight against terrorism it has become obvious that the traditional way of identifying individuals is insufficient. There are certain limits to the natural recognition process carried out by human beings: The recognition performance is not only impaired by difficulties with the recognition of people from other ethnic origin or deceptions due to a different hair-do or beards, but also by subjective impression based on a person’s outward.
The requirement of successful personal identification in access control and in other cases leads to using the results of biometrics. Biometrics Face recognition is a passive, non-invasive method for verifying the identity of a person, Offers the benefits of its unique facial technology in the form of customized overall solutions for the areas of access control, border control, ID-Management, search for criminals and video surveillance
Face recognition has come to be an active research area with numerous applications in recent years. In this thesis, a variety of approaches for face recognition are reviewed first. These approaches are classified according to basic tasks i-e Face Detect, face Normalization, and Face recognition. Then, an implementation of the face recognition method, the Eigenface recognition approach is presented in detail as well as other face recognitions methods i-e Local Feature Analysis, Neural Networks and Automatic face processing are discussed in general.
Ever since the birth of first mankind, human beings have continually been seeking for personal possessions. From the very basics of food and clothes, to cars, houses, and the more recent substantial property of data and information, it is becoming increasingly important that such valuable assets be sheltered by means of security control.
Throughout history, the types of technologies used on the access control systems are countless. From the traditional systems such as security guards checking personal ID’s to the very fundamentals of keypads and locks and password or entry code, the focus now has moved to the more advance technologies, particularly in today’s multifaceted society. Organisations are continuously seeking for a more secure, suitable and economical way of property protection.
The problem associated with traditional mechanisms is that the possessions could be lost, stolen, forgotten, or misplaced. Furthermore, once in control of the identifying possession, any other “unauthorised” person could abuse the privileges of the authorised user. Therefore there is a need of another approach to properly differentiate the correct (right) person from an impostor by positive identification of the person seeking access. Biometrics is one rising development in the field of access control system that provides true identification. Although the word “biometrics” sound very new and high tech, it is in fact the oldest form of identification known to man. Since the dawn of man, a persons face and voice was used to identify him/her. Before the digital age, a hand written signature was the only method used by a person to assert a unique form of identification that was difficult to copy. Popular biometric systems in use today include fingerprint recognition, iris recognition, voice recognition, and facial recognition systems. These systems are in practice in different organizations like banks, airports, social services offices, blood banks and other highly sensitive organizations. Biometric system offers the most accurate authentication solution and convenience. Biometrics systems can be integrated into any application that requires security, access control, and identification or verification of people. With biometric security, we can dispense with the key, the password, the PIN code; the access-enabler is human beings – not something he/she know, or something in his/her possession.
This part of the dissertation provides the general overview of biometrics. Definitions such as ‘Automatic’, ‘Physiological’ and ‘Behavioural’ characteristics are also discussed as well as different types of biometric systems i.e. one-to-one and one-to-many. General Biometrics Base systems model, how it works and Multimodal Biometrics systems are also discussed in detail.
In the last section of this chapter, a comprehensive overview of the right approach in selection of different technologies for an origination in terms of business objective, user acceptance, FFR, FAR, organisational environments, cost and a comparison of all biometrics are also presented.
Different types of biometric technologies are described in this chapter i.e. finger prints, iris and retina, voice, biometric signature and how these technologies work and the main features of these technologies with the help of diagrams.
This chapter is one of the most important chapters which explain the general back ground of face recognition technology and how face recognition works. It gives a brief discussion of how verification and identification is achieved with the help of face recognition system.
Actual techniques involved during face verification and identification i.e. faces detection, face normalisation and face recognition are also discussed in detail. Steps involved during the face detection i.e. coarse detection phase and refined search phase are discussed as well as how Normalisation is achieved through different steps i.e. lighting normalisation, scaling normalisation, rotation normalisation and background subtraction.
Face recognition and methods of face recognition i.e. Eigenfaces, feature analysis, neural network and automatic face processing are discussed in this presentation.
In this chapter of my dissertation, a proposed model of face recognition system for attendance of university students is discussed. The specification of the system is also compiled after the extensive study of face recognition products of different Vendors.
This final chapter of my dissertation contains the conclusion, future work and issues involved with face recognition system.
A review of the biometrics technology
Biometrics: An overview
In today’s networked and digital world the role of system security has a vital importance. In originations a large number of professional people are involved in one form of electronic transaction or another. Securing a company’s digital assets and identities is a necessity for financial success. Ignoring IT security increases the risk of losses for any company moving through this electronic world.
Logging on to a system by entering user ID and password is very simple but its simplicity makes serious security problems. There are, however, people who use ‘easy guess’ passwords or leave written passwords near to their computer. In this situation there is no way to confirm that the person is logged on the system using his/her ID and password or some one else, nothing can prevent someone else from accessing sensitive material. It’s like a passport system that doesn’t require a photograph. In addition, time consuming tasks behind the management of user ID and passwords divert already insufficient resources from other important responsibilities.
Establishing an accurate identity is the main focus of the information systems security in recent years and great efforts are made in this field. Two types of identification systems are in use now today.
- In one type identification system flawed identity checking results in unnecessary duplication, fraud and client disruption, resulting costs and risks.
- While in other type of identification system an accurate identification procedure and effectiveness may be undermined by unpopularity resulting falsification and evasion.
Three conventional forms of identification are in use.
- Origination ID or smart cards.
- The use of passwords or Personal Identification Number’s, mother name, place of birth, home address etc.
- The third form of identification is to identify something unique about a person, such as fingerprints, voice recognition, hand geometry, face structure, iris and retina. This third form of identification is known as ‘Biometrics’.
Biometrics is a branch of science in which we study, what makes us biologically unique. It is also referred to the science and application of statistical analysis of biological characteristics (Physiological/ Behavioural). In security terms, Biometrics refers to technologies that analyse human characteristics for security purposes. Therefore Biometrics technologies are concerned with the physical parts of the human or personal trait of human being.
There are different definitions of security base biometrics that have been circulating for a numbers of years.
According to Ashbourn, an expert in Biometrics, “Biometrics is a measurable physiological and / or behavioural trait that can be captured and subsequently compared with another instance at the time of verification”). 
The Biometrics Consortium states “Biometrics is automated methods of recognizing a person based on a physiological or behavioural characteristic”. 
The international Biometrics Group defines biometrics as “the automated use of physiological or behavioural characteristics to determine or verify identity” 
- Physiological characteristics are fingerprint, Hand geometry, iris pattern ,retinal, ear shape and facial scans etc
- Behavioural characteristics are voice pattern, key strokes, signature etc.
As mentioned, biometric technologies are anxious with the physical parts of the human or personal mannerism of human beings. The word “automatics” basically means that biometrics technology must recognise to identify /verify human characteristics rapidly and automatically, in real time.
Unique physiological characteristics or behavioural mannerisms are examined in biometrics verification for an individual’s identity. Physiological characteristics are essentially unchangeable such as hand geometry, iris pattern , palm prints, face structure and vane shape etc .while behavioural characteristic such as one’s signature, voice or keystroke dynamics are changeable and these behavioural characteristics can change over time. They are both controllable and less controllable actions.
The initial sample of the biometrics template, which is stored in the data base during the Enrolment, must be updated each time it is used. Although behaviour characteristics based biometrics is less costly and less intimidating to users, physiological characteristics have a tendency to offer greater accuracy and security. In any case, both techniques grant an extensively higher level of identification and verification as compare to smart cards or passwords technologies.
A password or personal identification number (PIN) is not unique for an individual ,it can be stolen ,forgotten or lost, while a biometric characteristic is unique to each individual; it can be used to prevent fraud or theft. It cannot be lost, stolen or forgotten.
There already many places such as research laboratories, defence (military) installations, VIP offices, day care centres and cash points where access is guarded by biometrics base authentication system.
The following biometric identifiers currently obtainable or under development are fingerprints, body aroma, ear shape, face recognition, keystroke dynamics, palm print, retinal scan, iris pattern, signature, DNA, “vein check” and voice pattern.
A biometric based system is a system that in some way uses physical characteristics or personal traits of a human being. These systems are not only, mainly used for security, but also use for encryption.
The processes of translating a message (plaintext), with the help of software, into a programmed message/encoded text (Cipher text), called Encryption. This is usually accomplished using a secret key and a cryptographic code. 
Type of Biometrics-based Systems
There are two types of Biometrics-based systems.
One-to-one systems (Verification system)
One-to-many systems (Identification System)
One-to-one system (verification)
This type of biometric system works on the base of one to one matching and authentication principles where the system asks and attempts to answer the question “Am I who I claim to be?” At first a biometric sample of a person is provided to the system and then the system matches this sample to the previously stored template during the enrolment mode for that person. The system then decides whether that is the person who claims the identity. After a successful matching of the fresh sample with the stored template, the system authenticates the person. These types of systems are also referred to as verification systems. The verification system is a fast response system because it minimises the use of resources and time by providing biometrics sample/ information to the system which specifies the stored template in the data base for that person. 
One-to-many system (identification)
This type of biometrics system works on the base of one to many recognition principles. The system attempts to answer the question,” Who am I?” The basic purpose of this system to identify a person’s identity by performing matches against all biometrics templates stored in a data base or a data library. A person does not claim his/her identity to the system; instead the person just gives the system some biometric data. The system then performs to match this data to all templates previously stored in the database and decides whether a match can be made. It is not necessary that the system responds with the person’s name, it could be the person’s ID or other unique identity. These types of systems are referred to as identification systems . Identification systems have a slow response as compared to verification systems. This is because they require much more powerful resources due to the fact that more comparisons are required by identification systems.
The biometrics identification system also prevents a person from registering twice on the system and ensures that a person is not already present in a data base. This type of system can be used in a large scale public benefits organisation, such as being used at banks where a person would try opening a second account on another name. This system can also be used with immigration where a person could try to enter the country on false documents.
General Biometrics Base Authentication System Model
A general biometrics base authentication system model consists of three major components, hardware, software and interface. Hardware is used to capture the biometrics information and software is used to maintain and manage it while an interface with application system that will use the result to confirm an individual’s identity. The system operates in two different modes:
- Enrolment mode
- Authentication mode
In this mode a user’s biometrics data is provided to a system, which stores this user’s biometric sample in a database or data library as a template. Hardware such as a biometrics readers/ scanners, cameras are used to capture biometrics sample. This stored template is then labelled with a user identity e.g. name, identification number etc.
The way biometrics operate
Some biometric base authentication systems may need a number of biometrics samples in order to build a profile of the biometric characteristics. These exclusive characteristics are then extracted and changed in to mathematical code by the system. Which is then stored in to the biometric system as a biometric template for the person who enrolled? The template is store in the memory storage of the system, or in computer database, smart card or barcode. A threshold is set in to the biometrics base authentication system according to the level of security , (a high threshold is set for high level of security)
To secure the template to the person, a trigger or other mean of securing such as personal identification number, or a smart card that store the template which read by a card reader during the authentication mode, are use in biometrics. In some biometrics system when ever a person interacts with the system a new biometrics sample is provide to the system which is compared to the template. If this new sample and stored template is match (the score of new match if exceed from the set threshold then access is granted to that person).
As both physical and behavioural characteristics are inconsistent with time, this change may be due to the age of the person, general health condition, working and environmental conditions and time pressures etc. the biometric base authentication system must allow for these delicate changes, in this case before a match is recorded a threshold *1 is set. This can take the form of an accuracy score *2. The comparison between the template and new sample must exceed this set threshold. If it not exceeds the system will not record the match and will not identify the person.
This use of a threshold gives biometric technologies a significant advantage over passwords, PIN’s and ID badges. The use of a threshold affords a tremendous degree of flexibility and if the comparison between the new biometric sample and the template exceeds the stated threshold, identity will be confirmed.
- Threshold:-a predefine number, often controlled by system administer, which establish the degree of correlation necessary for a comparison to be deemed a match.
- Score: – A number indicating the degree of similarity or correlation of a biometrics match
Capture, extraction, comparison and match/non match are the four stages use by all biometric authentication systems.
- Capture – A physical or behavioural sample is captured by the system during enrolment.
- Extraction – unique data is extracted from the sample and a template is created.
- Comparison – the template is then compared with a new sample.
Multimodal Biometric System
In some environments a signal biometrics identifier base system such as finger scan, face scan or iris scan etc often not able to meet the desired performance requirement of the organization. Different biometrics base identification system such as face recognition, finger print verification and vice verification, is integrated and worked as a single biometrics base identification system. Multimodal biometrics base identification system is use to over come the limitation of the single identifier biometrics base identification system.
Initial experimental results reveal that the identity established by such an integrated system is more reliable than the identity established by a signal biometrics identifier base system. 
Selecting the Right Approach
In Different Environment Different biometrics base authentication systems are used. To choose the right approach to biometrics authentication it is necessary to understand the requirement of the organisation, the application of the biometrics system, and characteristics of the biometrics devices itself.
Following factors are also important to choose a biometrics base authentication system, which most devices can’t store raw fingerprints and that fingerprints can’t be reconstructed based on the data stored within these systems. Intrusiveness is another factor affecting user acceptance of some devices, particularly iris and retinal scanning systems. 
Business objective of the organisation
The most important aspect to consider when selecting a biometrics base authentication system is the organisation business’ objectives. The choice biometrics system must meet or exceed organisational business objectives as well as sustain organisation in the coming years. Business objective is the bottom line where organisation starts and end.
Some biometrics, such as fingerprints, may be apparent as an assault of personal privacy. The system must not associate with other govt agencies biometrics (finger print) recognition system that most devices can’t store raw fingerprints and that fingerprints can’t be reconstructed based on the data stored within these systems. General intrusiveness can be another factor affecting user acceptance of some devices, particularly iris and retinal scanning systems. Following are the errors of biometrics base authentication system.
False acceptance rate (FAR)
False acceptance rate (FAR) is a system error. It is the rate at which an interloper can be recognized as a valid user. In one -to-one match during user verification, false acceptance is based on fake attempts, not on the total number of attempts by valid users.
If FAR is 1%, it means one out of 100 users trying to break into the system will be successful . FARs become more critical when you attempt to identify users based on biometrics, instead of simply trying to verify a person with a one-to-one or one-to-few operation
False reject rate (FRR)
False reject rate (FRR) is another type of error of biometrics system. It is the rate at which a valid user is rejected from the system. Consider a finger print recognition system; unfortunately, the conditions under which the original sample was collected can never be exactly duplicated when the user submits subsequence biometrics information to be compared. False reject rate may occur due to following variations.
- Rotation and Translation because of different positioning of the finger on the finger print device.
- Downward pressure on the surface of the input device which changes the scale of input device.
- Non-permanent or semi-permanent distortions like skin disease, scars, sweat, etc
To over come FRR it is essential that all biometrics base authentication systems have a threshold value in order to allow for minor differences.
With out threshold value FRR occurs and valid users will be probably rejected by system. If the threshold value is too high FAR occur . It is there for necessary to find a proper threshold value.
As stated it is important to consider the organisational environment when selecting biometrics base authentication system. Users with wet, dirty or dry hand have experienced problems with finger and palm recognition system. People using gloves generally can’t use these systems. Face recognition system can’t be easily be used in medical environments where hood and masks are used by users.
The direct cost of the system (hardware and software) is the initial considerations. Due to the improvement of features and functionality the over all cost of biometrics system reduces. It not only reduces fraud and eliminating problems associated with stolen or forgotten passwords but also reduces the help desk role.
The subject of this chapter is biometrics, which is defined as “…a method of verifying an individual’s identity based on measurement of the individual’s physical feature(s) or repeatable action(s) where those features and/or actions are both unique to that individual and measurable”.
A biometrics system which consists of enrolment mode and authentication mode, unique physiological characteristics or behavioural mannerisms are examined in biometrics verification for an individual’s identity. All biometric systems essentially operate in a similar way in a four-stage process that is automated and computerized which are Capture, Extraction, Comparison and Match/non-match.
Biometrics system one-to-one is based on one to one matching and authentication principles and is mainly used for verification purposes, while biometrics system one to many works on the principles of one-to-many recognition and is used for identification.
Multimodal biometrics base identification system is used to over come the limitation of the signal identifier biometrics base identification system in which different biometrics base identification system such as face recognition, finger print verification and vice verification, is integrated and worked as a single biometrics base identification system.
Methodologies of Biometrics Authentication
As stated, different biometric systems are use in different organisations according to their requirements. The most common biometrics system in use today includes fingerprint recognition, iris recognition, and voice recognition and face recognition systems. There are also other biometric systems available like retina recognition, vein pattern recognition, signature and DNA matching systems. These systems are not as widely used yet for various reasons.
These biometrics systems can be integrated into any application that requires security, access control and identification or verification of people. With biometric security we can dispense with the key, the password and the PIN code; the access-enabler is a person, not something person know or something in his /her possession. Biometrics systems secured resources are based on who a person is. Biometrics systems also minimise the risk that is associated with less advanced technologies while at the same time offering a higher level of security and convenience.
Fingerprint Recognition System
Fingerprints are one of the human physiological characteristics that do not change throughout someone’s life. Even identical twins have different fingerprint patterns. The chance of identical twins to have the same fingerprint is less than one in a billion. Fingerprint recognition is generally considered the most practical system for its reliability, non-intrusive interfaces, and cost-effectiveness. In recent years, fingerprints have rallied significant support as the biometric technology that will probably be most widely used in the future. In addition to general security and access control applications, fingerprint verifiers are installed at different organisations such as, defence/military organisations health care, banking and finance, application services providers, immigration, law enforcement etc.
The fingerprint’s strength is its acceptance, convenience and reliability. It takes little time and effort for somebody using a fingerprint identification device to have his or her fingerprint scanned. Studies have also found that using fingerprints as an identification source is the least intrusive of all biometric techniques. 
Verification of fingerprints is also fast and reliable. Users experience fewer errors in matching when they use fingerprints versus many other biometric methods. In addition, a fingerprint identification device can require very little space on a desktop or in a machine. Several companies have produced capture units smaller than a deck of cards.
One of the biggest fears of fingerprint technology is the theft of fingerprints. Skeptics point out that latent or residual prints left on the glass of a fingerprint scanner may be copied. However, a good fingerprint identification device only detects live fingers and will not acknowledge fingerprint copies.
Main Feature of Finger print verification system
- Analysis of minutia points i.e. finger image ridge (verification) endings, bifurcations or branches made by ridges.
- One of the most commercially successful biometric technologies.
- Important for applications where it is necessary to verify the identity of those who gain access.
How fingerprint recognition system works
In biometrics systems fingerprint recognition system is the fastest verification /identification (One-to-One / One-to-Many) system as shown in figure 3, 4, 5. Like other biometrics recognition systems it performs fingerprint recognition with the help of specialised hardware. This specialised hardware is supported by the conventional computer hardware and special software. All biometrics systems operate in two modes, enrolment mode and authentication mode (as discussed in the previous chapter). A sample of the fingerprint of a live person is provided to the system which is then converted into mathematical code (Template) and stored for the enrolee into the database.
In the first step of the authentication process, a fingerprint impression is provided to the system. The system takes a digital image (input image figure 3:1:1 below) using different techniques including scanner, optical, and ultrasound or semiconductor chip technologies. The digital image of the fingerprint includes several unique features in terms of ridge bifurcations and ridge endings, collectively referred to as minutiae. 
In the next step the system uses an automatic feature extraction algorithm to locate these features in the fingerprint image, as shown in Figure 3:1:2.
Each of these features is commonly represented by its location (x, y, and z) and the ridge direction at that location; however the feature extraction stage may miss some minutiae and may generate spurious minutiae due to sensor noise and other variability in the imaging process. The elasticity of the human skin also affects the feature extraction process. 
In the final stage, a final decision of match and non match is made on the bases of similarity between the two sets of features after compensating for the rotation, conversion and dimension. This similarity is often expressed as a score. A decision threshold is first selected. If the score is below the threshold, the fingerprints are determined not to match; if the score is above the threshold, a correct match is declared an authentication is granted to the person.
Iris and Retina Recognition System
Biometrics which analyse the intricate and unique characteristics of the eye can be divided into two different fields, Iris and Retina. Iris and retinal scans both deal with the human eye. They are done in an extremely different way as compared to other biometrics technology.
Iris Recogniton System
Iris recognition biometrics base authentication systems have unique characteristics and features of the human iris used to verify the identity of an individual. The iris is the area of the eye where the pigmented or colour circle, usually brown or blue, rings the dark pupil of the eye. It consists of over 400 unique distinguishing characteristics that can be quantified and used for an individual identity. However, only about 260 of those characteristics are captured in a “live” iris identification process . Iris’ are composed before birth and, except in the event of an injury to the eyeball, remain unchanged throughout an individual’s lifetime. Eyeglasses and contact lenses present no problems to the quality of the image and the iris recognition /scan systems test for a live eye by checking for the normal continuous fluctuation in the pupil size. As Iris patterns are extremely complex and unique they carry an astonishing amount of information. The fact that an individual’s right and left eye are different and that patterns are easy to capture, it establishes iris recognition
Cite This Work
To export a reference to this article please select a referencing stye below:
Related ServicesView all
DMCA / Removal Request
If you are the original writer of this dissertation and no longer wish to have your work published on the UKDiss.com website then please: