In a biometric verification system of a smart
gun, the rightful user is recognized based on his handpressure pattern. The main factor which affects the
verification performance of this system is the variation
between the probe image and the gallery image of a
subject, in particular when the probe and the gallery
images have been recorded with a few weeks in between.
One of the major variations is in the pressure distribution
of images. In this work, we propose a novel preprocessing
technique, Local Absolute Binary Patterns, prior to grippattern classification. With respect to a certain pixel in an image, Local Absolute Binary Patterns processing
quantifies how its neighboring pixels are fluctuating.
It will be shown that this technique can both reduce
the variation of pressure distribution, and extract information of the hand shape in the image. Therefore, a significant improvement of the verification result has been achieved.
|Title of host publication||IEEE conference on Biometrics: Theory, Applications and Systems|
|Editors||K.W. Bowyer, P.J. Flynn, V. Govindaraju, N. Ratha|
|Place of Publication||Los Alamitos, CA, USA|
|Publisher||University of Notre Dame|
|Number of pages||6|
|Publication status||Published - 29 Sep 2007|
|Event||First IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2007 - Washington, DC, USA|
Duration: 27 Sep 2007 → 29 Sep 2007
|Conference||First IEEE International Conference on Biometrics: Theory, Applications and Systems, BTAS 2007|
|Period||27/09/07 → 29/09/07|
|Other||27-29 September 2007|