Sensor B in Action

This weekend, we were able to test Sensor B (generic TIR sensor). In comparison to our MSI sensor, the images are faded and not as significant. Below are some examples of the images





















So on the left is an enrollment of a fingerprint into its database. The sensor requires four different scans of the fingerprint. Then on the right is the verification process, which can be done recursively as many times as wanted. The panel on the right side will display whether the finger scan matched the enrolled fingerprint. Here you can see a number of VERIFIED messages, a few that did not register (the sensor did not sense a finger on the platen). And the last one is a failure (where the correct finger was placed but the sensor did not verify). The region that made contact on the platen was the tip of my finger.

TIR sensors are so picky....

There are certain conditions that TIR sensors require to get good quality images. These conditions are the following:

• Good contact between the finger and the platen
• Fingerprint features are well defined
• Skin has a proper index of refraction
• There is no water, oil or other contaminant on the platen
  

Below are some generic samples that were collected (using the fingerprint sensor described in Fingerprint Enhancement Using a Multispectral Sensor)


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Further Analysis of TIR sensor technology

The source of light is generally from LED's (light emitting diodes) that are located on the left side of the prism. This light then reflects off of a diffuse reflective coating that is located on the right side, causing the upper region of the prism (the platen) to light up. If there is no finger placed on the platen, the light will reflect off the platen due to total internal reflectance. There is an imaging system in the lower left side, which will create the image of the top horizontal platen. So when a finger is placed on the platen, the light will cross the valley’s of the fingerprint and cause TIR at these “valley” like locations. So the image that is processed will have dark features where there is contact with the ridges, and lighter features where there is none.

Sensor A vs Sensor B

To further proceed with our research, we need to do a quick comparison and discuss the differences and similarities of two sensors.

Features of Sensor A

• Utilizes Multispectral imaging
• Flexible, powerful device outputs
• Compact design
• Pixel Resolution 500 dpi
  
• State-of-the-art prevention technology
• Expansive operating range

Features of Sensor B

• Utilizes optical fingerprint scanning technology
• Superior ESD resistance
• Small form factor
• Excellent image quality
• Encrypted fingerprint data
• Latent print rejection
• Counterfeit finger rejection
• Rotation invariant
• Rugged
• Works well with dry, moist, or rough
fingerprints
• Compatible with Windows® Vista,
XP Professional, 2000 and Windows
Server 2000, 2003

Key Specifications

• Pixel resolution: 512 dpi (average x, y
over the scan area)
• Scan capture area: 14.6 mm (nom.
width at center) 18.1 mm (nom.
length)
• 8-bit grayscale (256 levels of gray)
• Reader size (approximate): 79 mm x
49 mm x 19 mm
• Compatible with USB 1.0, 1.1 and 2.0
(Full Speed) specifications
• Indoor, home and office use

EUReKA

Every year, Jacobs School of Engineering gives undergraduate students the opportunity to showcase their research at Engineering Undergraduate Research Konference & Assembly (EUReKA). Karan and I decided to participate in this annual event by making a poster about our ongoing project especially since this year EUReKA will coincide with the Corporate Affiliates Program (CAP) board meeting in the Fung Auditorium, which could be an opportunity to get job offers from companies' representives presented at the CAP meeting. So this is a great opportunity to describe our research project, its implications, and results to-date.

What Are Fingerprint Minutiae

Fingerprints are known to be unique to every individual. A Minutiae is defined as: the points of interest in a fingerprint, such as bifurcations (a ridge splitting into two) and ridge endings. Types of ridges:

• ridge endings - a ridge that ends abruptly
• ridge bifurcation - a single ridge that divides into two ridges
• short ridges, island or independent ridge - a ridge that commences, travels a short distance and then ends
• ridge enclosures - a single ridge that bifurcates and reunites shortly afterward to continue as a single ridge
• spur - a bifurcation with a short ridge branching off a longer ridge
• crossover or bridge - a short ridge that runs bbetween two parallel ridges

Relevant papers:
www.research.ibm.com/ecvg/pubs/aws-constructive.pdf

MSI vs TIR

This week we read up a little bit more on Multispectral images (MSI) and total internal reflection images (TIR). The way that these MSI scanners are programmed is that they integrate both the capabilities of MSI and TIR images when the user places his or her finger on the scanner. The multispectral images are processed to enhance the fingerprint minutiae. Both MSI and TIR images are then passed into the the SDK for the scanner to detect the minutiae in the fingerprint.

Similarities:

1. Light Source - provides the light for our sensor to illuminate the platen on top of which the finger rests.
2. Imaging System – creates the digital imaging array from the image pn the platen.

Differences:

• MSI - The orientation of the light source and imagers do not exceed any critical angle conditions.
• TIR – In normal TIR sensors, the light strikes a medium larger than the critical angle.
• MSI - Has multiple illumination wavelengths,
• TIR - Monochromatic illumination system.
• MSI - uses polarizers that are arranged orthogonally to highlight the light that penetrates the skin surface. Once the light penetrates the skin surface, it undergoes multiple scattering events, once the light exits the skin it makes its way to the image array

Full Research Description of this is found in the following papers:

1. Multispectral Fingerprint Biometrics

2. Fingerprint enhancement using a multispectral sensor