Fingerprint Feature Extraction

Once a high-quality image is captured, there are a several steps required to convert its distinctive features into a compact template. This process, known as feature extraction, is at the core of finger-scan technology. Each of the 50 primary finger-scan vendors has a proprietary feature extraction mechanism; the vendors guard these unique algorithms very closely. What follows is a series of steps used, in some fashion, by many vendors - the basic principles apply even to those vendors who use alternative mechanisms.

The image must then be converted to a usable format. If the image is grayscale, areas lighter than a particular threshold are discarded, and those darker are made black. The ridges are then thinned from 5-8 pixels in width down to one pixel, for precise location of endings and bifurcations.

Minutiae localization begins with this processed image. At this point, even a very precise 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 caused by scars, sweat, or dirt appear as false minutiae, and algorithms locate any points or patterns that don't make sense, such as a spur on an island (probably false) or a ridge crossing perpendicular to 2-3 others (probably a scar or dirt). A large percentage of would-be minutiae are discarded in this process.

 

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The most comprehensive and up-to-date information on finger-scan technology - the market, technology and applications - can be found in IBG's authoritative report on the "State of Fingerprint Technology."