Home About Us Contact Us Inquiry Cart Support

Security Systems

Fingerprint Biometrics

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:

  • Minutia matching compares specific details within the fingerprint ridges. At registration (also called enrollment), the minutia points are located, together with their relative positions to each other and their directions. At the matching stage, the fingerprint image is processed to extract its minutia points, which are then compared with the registered template.
  • Pattern matching compares the overall characteristics of the fingerprints, not only individual points. Fingerprint characteristics can include sub-areas of certain interest including ridge thickness, curvature, or density. During enrollment, small sections of the fingerprint and their relative distances are extracted from the fingerprint. Areas of interest are the area around a minutia point, areas with low curvature radius, and areas with unusual combinations of ridges.

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

  • Easy to use
  • Cheap
  • Small size
  • Low power
  • Non-intrusive
  • Large database already available

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 Indentification 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.

Fingerprint Recognition: Strengths
  • Most widely used technology
  • Proven technology capable of high accuracy
  • Ability to enroll multiple fingers
  • Wide range of deployment environments
Fingerprint Recognition:Considerations
  • perception of law enforcement, forensic uses
  • Impaired or damaged fingerprints
  • May Require additional hardware and software
  • Standards needed for interoperability
Iris recognition: Strengths
  • Highly reliable, hands-free operation
  • High stability of characteristics over lifetime
  • Iris is a rich source of biometric data
  • Successful tests in air travel
Iris recognition: Considerations
  • Acquisition of iris image requires more training and attentiveness than most biometrics
  • Hardware and software licensing costs
  • Glasses with strong lenses may impact performance
  • Potential for false non-matching
Hand Geometry: Strengths
  • Able to operate in challenging environments
  • Established, reliable core technology
  • Perceived as non-intrusive
Hand Geometry: Considerations
  • Design complicates usage by certain population
  • Perception of bio-hazard, passing gems
  • Possible hand changes over time
Face Recognition: Strengths
  • May operate without user compliance
  • Leverage existing image databases
  • Only technologu capable of identification at a distance and surveillance
Face Recognition: Considerations
  • Susceptible to high false match rates in one-to-one and one-to-many applications
  • Lighting, camera angle reduce matching accuracy
  • Changes in physiological characteristics reduce matching accuracy
Technology
Characteristic
Fingerprint Iris Facial Hand
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,
30 seconds
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%
False match
rate(FMR)c
0%to8% Less than 1% 0.3%-5% 0%-2.1%
User acceptance issues Associated with law
enforcement,
hygiene concerns
User resistance,
usage difficulty
Potential for privacy misuse Hygiene
concerns
factors affecting
Performanced
Dirty, dry or worn
fingertips
Poor eyesight, glare, or reflection Lighting, Orientation of face and sunglasses Hand injuries, arthritis, swelling
Demonstrated
vulnerabilitye
Artificial fingers,
reactivated latent
prints
High-resolution picture of iris Notebook computer with digital photographs None
Variability with agesf Stable Stable Affected by aging Stable
Commercial availability
since
1970s 1997 1990s 1970s
  1. (a) Amount of time it takes to verify machine-red biometric versus stored biometric.
  2. (b) The probability that individuals who should be matched are not matched by a biometrics system.
  3. (c) The probalility of an erroneous match in a singgle template comparison.
  4. (d) Human characteristics or measurement condition circumstances that could adversely affect accuracy of biometric systems.
  5. (e) Demonstrated methods of beating biometric systems that have benn employed in tests.
  6. (f) Effects of age, if any, of individual on his or her biometric identifiers.

 

Security Cameras

Security cameras are of different types. One of them is closed circuit television, popularly known as CCTV. CCTV cameras are in use since 1942. Security cameras represent best mode of surveillance and security. CCTV cameras are no exception. They have become a common feature in many shopping premises, corporate buildings, malls, multiplexes, and other important buildings. Interestingly, they have also been used to monitor processes like nuclear fuel and industrial manufacturing.

Recent times have witnessed great improvement in the functioning of CCTV camera. They are not just cameras providing real time feeds but they have also gone digital. Shutter speeds have increased tremendously. Pixel resolution is impressive and memory capacity has enhanced greatly.

Now a day, CCTV cameras take photographs on a continuous basis as well as when alerted by a motion detector. Set up has become very easy and that has further increased its popularity. Additional feature of storing images on computers from CCTV cameras has made these cameras even more appealing. CCTV cameras are available in low as well as high end segment. One can opt for his preferred CCTV cameras based on his requirements.

Home / Computer and Software/ Home Appliances/ Services & Solutions/ About Us/ Contact Us
Copyright © 2011 Compucat Technologies. All rights reserved.