| dc.description.abstract |
In this paper, a new approach for user recognition is presented,
which is based on the geometric features from either left or right hand images.
The hand images are collected at unconstrained pose environment. Image
normalisation is applied at the preprocessing stage. Features are extracted from
the normalised images, which are mainly comprised of lengths and widths at
different positions of the fingers. A simple classification algorithm has been
implemented that is primarily dependent on the ratio of modified minimum
distance and number of features, which are matched within a distance
threshold. Experimental results of identification and verification are quite
acceptable, producing 98.8% identification and 99.6% verification (at 0.55%
FAR) of 253 standard subjects which are a blend of both left and right hand
images. |
en_US |