One way to identify a person is to measure the unique geometry
of their hand. This is an attractive biometric because it is
minimally invasive and has no criminal stigma associated with it
(unlike fingerprints).
Feature extraction involves computing the widths and lengths of
the fingers at various locations using the captured image.
These metrics define the feature vector of the user's hand. Current
research work involves identifying new features that would result
in better discriminablity between two different hands, and
designing a deformable model for the hand.
In our system the image acquisition system comprises of a light source, a camera, a single mirror and a flat surface (with five pegs on it). The user places his hand - palm facing downwards - on the flat surface of the device. The five pegs serve as control points for an appropriate placement of the right hand of the user. The device also has knobs to change the intensity of the light source and the focal length of the camera. The lone mirror projects the side-view of the user's hand onto the camera. The device is hooked to a PC with a GUI application which provides a live visual feedback of the top-view and the side-view of the hand. The GUI aids in capturing the hand image. |
| Contact: Sharath Pankanti | Last updated: 6/7/02 | ||
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