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