ABSTRACT
With
the increase in technology threat to personal data and national security had also
increased. The methods that were developed to secure important information from
outside intervention were not up to safe mark .There was a need to introduce a
technology that secures our data more efficiently from unlawful intervention.
We developed a palm vein pattern authentication technology that uses vascular patterns
as personal identification data .Vein recognition technology is secure because the
authentication data exists inside the body and is therefore very difficult to
forge. It is highly accurate. This technology can be used in various fields
like banking, hospitals, government offices, in passport issuing etc. Business
growth will be achieved with these solutions by reducing the size of the palm
vein sensor and shortening the authentication time.
Hand
vein is a biometric modality that seems promising as it is acquired in Near Infrared
light (NIR), which implies that skin variations and dirtiness are less sensible
than invisible light. Moreover, the haemoglobin which flows in the veins is
sensible to NIR light, this way allowing a good quality of acquisition of
the hand veins. It is possible touse either the back of the hand or the hand
palm. A recent study using back hand vein data and tested with 5 sessions per
person and 50 persons showed promising results. The main problem of this
database is the low resolution of the images (images at resolution132x124
pixels).The first commercialized products has been produced by Hitachi on the
back and Fujitsuon the palm. They claim a very low FRR (False Rejection Rate)
at very low FAR (False Acceptance Rate) on a huge database – close to 0% on
140000 hands. In general, in the various papers present in the literature,
after the acquisition phase, some matching algorithms are used such as the Line
segment Hausdorff Distance (LHD) method. TheLHD method has good experiment
results. But, the structure information of palm vein is not as clear as hand
vein, so line-based feature is not a good choice for palm vein recognition.
Matching based on minutiae analysis and Hausdorff distance (MHD) was used for
hand vein recognition. Minutiae-like feature could also be extracted from palm
vein pattern; however, the Hausdorff distance algorithm applied in minutiae
analysis is sensitive to the geometrical transformation. Besides P2PM, LHD and
MHD, all existing matching methods suffer from the problem of image rotation
and shift. Therefore, it is necessary to develop a new matching method which
can effectively solve this problem. This paper presents a new and efficient
matching method by introducing the iterative closest point (ICP) algorithm into
palm vein verification. The ICP algorithm was firstly proposed by Besl and
McKay and it was originally used in the registering of three-dimensional (3D)
range images. It is also well suited to align two dimensional (2D) images. This
paper is about the palm vein technology, its applications, how this technology
is applied in real time applications and the advantages of using this
technology
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