Principles of fingerprint biometrics
A fingerprint is made of a a number of ridges and valleys on the surface of the finger. Ridges are the upper skin layer segments of the finger and valleys are the lower segments. The ridges form so-called minutia points: ridge endings (where a ridge end) and ridge bifurcations (where a ridge splits in two). Many types of minutiae exist, including dots (very small ridges), islands (ridges slightly longer than dots, occupying a middle space between two temporarily divergent ridges), ponds or lakes (empty spaces between two temporarily divergent ridges), spurs (a notch protruding from a ridge), bridges (small ridges joining two longer adjacent ridges), and crossovers (two ridges which cross each other).
The uniqueness of a fingerprint can be determined by the pattern of ridges and furrows as well as the minutiae points. There are five basic fingerprint patterns: arch, tented arch, left loop, right loop and whorl. Loops make up 60% of all fingerprints, whorls account for 30%, and arches for 10%.
Fingerprints are usually considered to be unique, with no two fingers having the exact same dermal ridge characteristics.
How does fingerprint biometrics work
The main technologies used to capture the fingerprint image with sufficient detail are optical, silicon, and ultrasound.
There are two main algorithm families to recognize fingerprints:
Issues with fingerprint systems
The tip of the finger is a small area from which to take measurements, and ridge patterns can be affected by cuts, dirt, or even wear and tear. Acquiring high-quality images of distinctive fingerprint ridges and minutiae is complicated task.
People with no or few minutia points (surgeons as they often wash their hands with strong detergents, builders, people with special skin conditions) cannot enroll or use the system. The number of minutia points can be a limiting factor for security of the algorithm. Results can also be confused by false minutia points (areas of obfuscation that appear due to low-quality enrollment, imaging, or fingerprint ridge detail).
Note: There is some controversy over the uniqueness of fingerprints. The quality of partial prints is however the limiting factor. As the number of defining points of the fingerprint become smaller, the degree of certainty of identity declines. There have been a few well-documented cases of people being wrongly accused on the basis of partial fingerprints.
Benefits of fingerprint biometric systems
Applications of fingerprint biometrics
Fingerprint sensors are best for devices such as cell phones, USB flash drives, notebook computers and other applications where price, size, cost and low power are key requirements. Fingerprint biometric systems are also used for law enforcement, background searches to screen job applicants, healthcare and welfare.
Fingerprint Identification Systems
Fingerprint Identification is the method of identification using the impressions made by the minute ridge formations or patterns found on the fingertips. No two persons have exactly the same arrangement of ridge patterns, and the patterns of any one individual remain unchanged throughout life. Fingerprints offer an infallible means of personal identification. Other personal characteristics may change, but fingerprints do not.
|How it works||Capture and compares fingertip s patterns||Captures and compares iris patterns||Captures and compares facial patterns||Measures and compare dimensions of hand and fingers|
|cost of device||Low||High||Moderate||Moderate|
|Enrollment time||About 3 minutes,|
|2 minutes, 15 seconds||About 3 minutes||About 1 minute|
|Transaction timea||9 to 19 seconds||12 seconds||10 seconds||6 to 10 seconds|
|False nonmatch rateb||.2%-36%||1.9%-6%||3.3%-70%||0%-5%|
|0%to8%||Less than 1%||0.3%-5%||0%-2.1%|
|User acceptance issues||Associated with law|
|Potential for privacy misuse||Hygiene|
|Dirty, dry or worn|
|Poor eyesight, glare, or reflection||Lighting, Orientation of face and sunglasses||Hand injuries, arthritis, swelling|
|High-resolution picture of iris||Notebook computer with digital photographs||None|
|Variability with agesf||Stable||Stable||Affected by aging||Stable|
- (a) Amount of time it takes to verify machine-red biometric versus stored biometric.
- (b) The probability that individuals who should be matched are not matched by a biometrics system.
- (c) The probalility of an erroneous match in a singgle template comparison.
- (d) Human characteristics or measurement condition circumstances that could adversely affect accuracy of biometric systems.
- (e) Demonstrated methods of beating biometric systems that have benn employed in tests.
- (f) Effects of age, if any, of individual on his or her biometric identifiers
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