An Introduction to Biometrics - Fingerprint Recognition
What is fingerprint recognition?
Fingerprint recognition consists of comparing a print of the characteristics
of a fingertip or a template of that print with a stored template or print.
How does it work?
A fingerprint consists of the features and details of a fingertip. There
are three major fingerprint features: the arch, loop and whorl. Each finger
has at least one major feature. Loops are lines that enter and exit on
the same side of the print. Arches are lines that start on one side of
the print, rise into hills and then exit on the other side of the print.
Whorls are circles that do not exit on either side of the print. The smaller
or minor features (or minutiae) consist of the position of ridge ends
(ridges are the lines that flow in various patterns across fingerprints)
and of ridge bifurcations (the point where ridges split in two). There
are between 50 and 200 such minor features on every finger [1]. Fingerprint
matching done on the basis of the three major features is called pattern
matching while the more microscopic approach is called minutiae matching.
Other features may be used for matching, but patterns and minutiae are
the main ones [2].

- Acquire a sample
Enrolment and acquisition can be done by sensors reading the tip of the finger directly and in real-time. A fingerprint scan contains a lot of information but scanners normally focus only on getting an image of the information that is essential for matching. The quality of the sensed fingerprint image is of key importance for the performance of the system. Given the small area of the fingertip, its detailed minutiae and its continuous use in everyday life (e.g. cuts, bruises, aging, weather conditions), poor image quality is a major concern in fingerprint applications.
There are three types of live scanners:- Optical devices using a light source and lens to capture the fingerprint with a camera;
- Solid-state sensors or silicon sensors appearing on the market in the mid-1990s to address the shortcomings of the early optical sensors [3];
- And others, such as acoustic sensors that use acoustic signals to detect fingerprint details.
- Extracting features
Getting a high quality image of the fingerprint is very important for accurate fingerprint recognition, but also feature extraction plays a crucial role. It consists of converting the fingerprint image into a usable and comparable format that does not require lots of storage space. The format or template is a compressed version of the fingerprint characteristics. Several approaches to automatic minutiae extraction exist, but most of these methods transform fingerprint images into binary images. This means that only the coordinates of the minutiae (30 or 40) are stored, reducing it to a few hundreds of bytes [4].
Feature extraction is also needed because even a very precise fingerprint image will have distortions and false minutiae that need to be filtered out. For example, an algorithm may search the image and eliminate one of two adjacent minutiae, as minutiae are very rarely adjacent. Anomalies can also be caused by scars, sweat, or dirt. The algorithms used for feature extraction filter the image to eliminate the distortions and would-be minutiae [5].
- Comparing Templates
The identification or verification process follows the same steps as the enrolment process with the addition of matching. It compares the template of the live image with a database of enrolled templates (identification), or with a single enrolled template (authentication).
- Declaring a Match
The comparison between the sensed fingerprint image or template against records in a database or a chip usually yields a matching score quantifying the similarity between the two representations. If the score is higher than a certain threshold, a match is declared, i.e. belonging to the same finger(s). The decision of a match or non-match can be automated but it depends also on whether matching is done for identification or verification purposes.
With identification applications, automated decision-making is possible when conditions are ideal. In the case of the Federal Bureau of Investigation (FBI) for instance, this means that fingerprint cards can be matched automatically when both enrolment and acquisition were done by law enforcement staff. But with latent prints (eg. collected at a crime scene), and prints with a lower quality image, the automated process is less reliable. Automated systems imitate the way human fingerprint experts work but the problem is that these systems can not have observed the many underlying information-rich features an expert is able to detect visually. Automatic systems are however, reliable, rapid, consistent and cost effective when matching conditions are good, but their level of sophistication cannot rival that of a well-trained fingerprint expert. Therefore, for instance a fingerprint expert can overrule an automated match [6].
Verification applications, especially mainstream commercial fingerprint verification may be, to a certain extent, less accurate because the issues at stake are different (e.g. identifying criminals), but also because verification consists of 1-1 matching. Verification may use less information from a fingerprint compared to forensic scientists identifying a fingerprint. The former seems to be more like a possible, "close-enough correlation" of similarities. Also, because of background interference (dirt, scratches, light, etc.), and no human supervision, the quality of fingerprint images is lower. The result is a "best" matching score which would not be feasible for law enforcement [7].
Applications
Fingerprint identification of criminals for law enforcement continues
to be one of the major applications domains for this technology. Another
large scale application in Europe is EURODAC for asylum requests. In New
York, fingerprints are used to prevent fraudulent enrolment for benefits.
Using fingerprint recognition to secure physical access is another popular
application. Moreover, embedding of fingerprint readers in electronic
devices opens up a whole range of digital applications that are based
on online authentication. Finally, decisions have been taken for the future
integration of fingerprints (with other biometrics) on travel documents
and passports.

The Integrated Automated Fingerprint Identification System, more commonly known as IAFIS, is one of the largest biometric database in the world. It is a US national fingerprint and criminal history system maintained by the FBI. It contains the fingerprints and corresponding criminal history information for more than 47 million subjects in the Criminal Master File. The fingerprints and corresponding criminal history information are submitted voluntarily by state, local, and federal law enforcement agencies. The IAFIS provides automated fingerprint search capabilities, electronic image storage, and electronic exchange of fingerprints and responses, 24 hours a day, 365 days a year [8]. In Europe, there is no such database. Criminal fingerprint databases are under control of national criminal authorities. The UK for instance, has a national automated fingerprint identification system (NAFI) containing more than four million records.
There is however, since January 2003, also a large central fingerprint database in the European Union, but for another purpose. It aims at preventing duplication of asylum requests in the EU Member states. EURODAC is an EU wide database (AFIS) set up to check the fingerprints of asylum seekers against the records of other EU countries. After one year of operation, an evaluation report on EURODAC highlighted satisfactory results in terms of efficiency, quality of service and cost effectiveness. The EURODAC central unit has been operating continuously. Within one year, it processed almost 250,000 fingerprints of asylum seekers. It detected 17,287 cases of multiple application (a same person having already made an asylum application in another country), which represents 7% of the total number of cases processed.
In addition to asylum requests, also illegal immigrants are identified. Almost 17,000 fingerprints of people in an illegal situation were detected and about 8,000 fingerprints related to attempts to cross borders illegally. The evaluation report also states that there were no data protection problems raised by the Member States' national data protection authorities regarding EURODAC operations [9].

The state of New York has over 900,000 people enrolled in a system which tracks entitlement to social services and protects against fraud known as double dipping, i.e. enrolling for a benefit under multiple names (OECD, 2004: 23). Fingerprint scanning is also being used to arrange secure access to schools and schools premises such as cafeterias and libraries. Finally, with the embedding of fingerprint scanners in electronic devices, online authentication (replacement of passwords, PINs, etc) becomes possible for a whole range of applications including electronic payments.
Finally, at EU level, the Council of European Ministers adopted the Regulation on mandatory facial images and fingerprints in EU passports at its meeting in Brussels on 13 December 2004. This Regulation applies to passports and travel documents issued by Member States (excluding Ireland, the UK and Denmark). After the Regulation is published in the Official Journal passports issued will have to contain a facial image within 18 months, and fingerprints within three years. Also a Committee will be set up by the European Commission with representatives from 22 Member States to decide on the details such as how many fingerprints are to be taken, the equipment needed and the costs [10].
Recommendations
- Making the fingerprint reader easier to locate
- Improving the accessibility of the fingerprint reader design
- Providing instructions in an accessible format
- Informing the user that the reader is waiting for him/her to take action
- Catering for users who do not require audio instructions (e.g. those who have good vision, or those who are familiar with the process)
Making the fingerprint reader easier to locate
- The scanner area should be lit internally. The light should only turn on when the reader is awaiting input or the light should start flashing slowly when the reader is awaiting input.
- Visually the reader should stand out if it is attached to a terminal. The reader could be highlighted by making it a different colour to the surrounding area.
- The reader should not be flush against the rest of the terminal. This will make it more noticeable from both a visual and a tactile point of view. The device as a whole should be raised from the terminal, with the scanner area itself slightly recessed into the raised surrounding casing.
Improving the accessibility of the fingerprint reader design
- A simple action should be required to enroll a fingerprint, such as simply pressing a finger on the scanner area and removing it. This is the action that 98% of the test subjects (including those who took part in either the pilot or the study) assumed they should use.
- Ideally the user should be able to simply press and hold the finger in place, while the multiple scans are taken in sequence (i.e. removing the necessity to lift and replace the finger repeatedly). This would cater for people with, for example, reduced manual dexterity or a hand tremor. However, if the movement of the hand is part of the authentication process (i.e. reducing the chance of the reader being fooled) this may not be an acceptable option.
- The reader should be centred on the terminal, so it is equally accessible for right- and left-handed people.
- Of the 40 test subjects in this study, two (5%) preferred to pick the reader up when they were using it. The remaining test subjects did not have any problem using the three readers flat on the desktop.
- Although the option of picking it up in one hand might be favourable for some, this may mean that the reader could be broken, stolen or simply in a different place every time the user goes to find it. Therefore having it fixed to the terminal would be preferable.
- Having the reader fixed to the terminal, but with an additional option of changing the angle at which it sits, could provide a viable compromise for the latter two problems.
- There should be a raised casing around the scanner area. This would allow the user to hold on to the casing, providing support for the repeated removal and replacement of the finger during the registration stage.
- The scanner area should be recessed into the surrounding raised casing, thereby guiding the finger into the correct location.
- Ideally, a tactile marking (consisting of, for example, a circular area with a different texture) in the very centre of the scanner area would allow accurate positioning of the finger, while at the same time not limiting the size of the scanner area, benefiting people with larger fingers.
Providing instructions in an accessible format
- If the terminal is unmanned, or an assistant is not always available to help the user, audio instructions should be provided, taking the user step-by-step through the enrolment and authentication process.
- Instructions should be provided, explaining any progress made.
For example, if a scan is successful: "This scan was successful, please remove your finger and place it on the reader again."
- Any further instructions explaining what the user is doing wrong would also be very helpful.
For example, if the scan is not successful: "This scan was not successful, please move your finger to the right."
or
"This scan was not successful, please hold your finger still on the reader."
- There should be a clear sound to indicate a success and a failure. A success should be signified by a higher more pleasant sound (e.g. chimes ringing), a failure by a lower less pleasant sound (e.g. buzz).
- When the first scan has been taken there should be an audible acknowledgement (such as a chime sound) followed by a spoken instruction: "The first scan has been successfully recorded. Please place your finger on the fingerprint reader for the second scan." And so on.
- There should be a clear indication when the registration process is complete. For example an audio message "Your fingerprint has been successfully registered."
- If the terminal is awaiting further information, the instruction should say this. If not, it should indicate that the user has reached the end of the process. For example "The registration process is now complete. Thank you."
- If registration fails, there should be a clear indication that the process will restart. For example "The registration has failed because the four fingerprint images did not match. The process will now restart. To enroll a fingerprint, you must have four successful scans. Please place your finger on the fingerprint reader for the first scan. Hold your finger still on the scanner area until you hear a chime."
Informing the user that the reader is waiting for him/her to take action
- The reader should be lit when it is awaiting input from the user.
- The reader should only light up when it is ready to enroll a fingerprint. When the process is complete the light should turn off.
- An audible message ("Please place your finger on the fingerprint reader") would help users who have insufficient vision to see the reader. See Section 4.2.3 above for more detailed guidelines on spoken instructions.
- A timeout feature on the terminal should not be excessively short, as the user may need an extended period of time to find the reader and to complete the required actions.
- If the user is taking an unusually long period of time to respond to an instruction the instruction should be repeated at least once before the terminal times out.
Catering for users who do not require audio instructions (e.g. those who have good vision, or those who are familiar with the process)
- An option to bypass the audio instructions should be provided. This could simply be that the audio comment is skipped or cuts out if the user provides the correct input.
Standards
Published standards:
- ANSI INCITS 377-2004: Information Technology-Finger Pattern Based Interchange Format
- ANSI INCITS 378-2004: Information Technology-Finger Minutiae Format for Data Interchange
- ANSI INCITS 381-2004: Information Technology-Finger Image Based Interchange Format
- ANSI/NIST-ITL 1-2000: Information Systems-Data Format for the Interchange of Fingerprint, Facial, & Tattoo (SMT) Information
- ISO/IEC 19794-4:2005: Information technology - Biometric data interchange formats - Part 4: Finger image data
- ISO/IEC FCD 19794-2: Information Technology-Biometric Data Interchange Formats-Part 2: Finger Minutiae Data
Standards under development:
- INCITS PN-1703-D: Information Technology- Conformance Testing Methodology for the Finger Minutiae Interchange Format
- INCITS PN-1705-D: Information Technology- Conformance Testing Methodology for the Finger Image Data Interchange Format
- ISO/IEC CD 19794-3: Information Technology-Biometric Data Interchange Formats-Part 3: Finger Pattern Spectral Data
- ISO/IEC WD 19794-8: Information Technology-Biometric Data Interchange Formats-Part 8: Finger Pattern Skeletal Data
Further information
- Fingerprint Guides and Articles
- Das, R, HTG Advance Solutions, An Application of Biometric Technology: Fingerprint Recognition
- BIOIDENITIFICATION - Fingerprint
- Biometrics at the Frontiers: Assessing the Impact on Society
- Fingerprint - Jean-François Mainguet
- Identification of Accessibility Issues for Visually Impaired Users of Biometric Technologies: Fingerprint Readers (RNIB Scientific Research Unit report)
Manufacturers/suppliers of fingerprint recognition technologies:
Accu-Time Systems Inc
Atmel Corporation
AuthenTec Inc
Bio-Key
BioMet Partners Inc
Biometric Technologies Ltd
Biometrika srl
Bioscrypt Inc
Cherry GmbH
Cogent Systems Inc
Deltabit
Oy
Dermalog Identification Systems GmbH
DigitalPersona Inc
EzValidation Inc
Human Recognition Systems
Identix
IDTECK Co Ltd
Lumidigm
Motorola
NEC
Neurotechnologija
NextgenID Ltd
onClick
Corp
Precise Biometrics
Recognition Systems
Saflink
Sagem Morpho Inc
SecureTech Solutions Inc
Texas
Instruments Inc
Touch Technology UK Ltd
Trifusion
TSSI Systems Ltd
UPEK
Validity Sensors Inc
Yarg Biometrics
[1] OECD, 2004: 21
[2] OGorman, L Fingerprint verification, in: A. Jain, Personal identification
in a networked society, Dordrecht: Kluwer Academic Publishers. R. Bolle
& S. Pankanti (eds.), 1999. pp. 43-64.
[3] Shortcomings are mainly size and cost. The chip sensors comprise an
array of sensing elements (each pixel is a sensor) that image the fingerprint.
Solid-state sensors have on-chip conversion (analogue to digital) so that
a digital image can be generated. There are mainly two types of solid
state sensors. Capacitive sensors are most prevalent and use electric
field strengths for distant measurement of fingerprint ridges and valleys.
Temperature sensors measure the temperature difference of a finger between
the skin ridges and the air (valleys).
[4] Mainguet, J-F. & Pégulu, M. & Harris, J-B. Fingerprint
recognition based on silicon chips, Future Generation Computer Systems,
16, 2000, pp 403-415.
[5]www.biometricgroup.com/reports/public/reports/finger-scan_extraction.html
[6] Jain, A. & Pankati, S. Automated
Fingerprint Identification and Imaging Systems, in Lee, H. & Gaensslen,
R. (eds.), Advances in Fingerprint Technology, 2nd Edition, Elsevier Science,
2001.
[7]onin.com
[8]www.fbi.gov/hq/cjisd/iafis.htm
[9] EURODAC detects 7% of multiple asylum applications during its first
year of activity; Press release by the European Commission, Reference
IP/04/581, 05/05/2004.
europa.eu.int:80/ida/en/document/2528
[10] EU Council Regulation on standards for security features and biometrics
in passports, 15152/04, 10 December 2004.
Acknowledgement
The information contained in this section was collected from the following source:
Kind permission was given by Bioscrypt Inc, Cogent Systems Inc, Deltabit Oy and Lenova for the use of the above pictures.
