Hand vein biometry based on geometry and appearance methods

Abstract

Many biometric systems, such as face, fingerprint and iris have been studied extensively for personal verification and identification purposes. Biometric identification with vein patterns is a more recent approach that uses the vast network of blood vessels underneath a person's skin. These patterns in the hands are assumed to be unique to each individual and they do not change over time except in size. As veins are under the skin and have a wealth of differentiating features, an attempt to copy an identity is extremely difficult. These properties of uniqueness, stability and strong immunity to forgery of the vein patterns make it a potentially good biometric trait which offers greater security and reliable features for personal identification. In this study, we present a novel hand vein database and a biometric technique based on the statistical processing of the hand vein patterns. The BOSPHORUS hand vein database has been collected under realistic conditions in that subjects had to undergo the procedures of holding a bag, pressing an elastic ball and cooling with ice, all exercises that force changes in the vein patterns. The applied recognition techniques are a combination of geometric and appearance-based techniques and good identification performances have been obtained on the database. Index TermsVein biometry, Hand vein database, Infrared imaging, BOSPHORUS hand vein database

Vein biometric security using irreversible curve fitting accounting for minimum storage

“…2 when translation of 2 is applied to query image. Algorithm was also tested on bosphorous hand vein dataset [10], vein pattern dataset by CIE biometrics, thermal images in [II] by wang and Liu, thermal focus image dataset by SP lab [12] [13]. Our algorithm was able to run properly on all of these images without any major changes.…”

Dorsal Hand Vein Pattern Analysis and Neural Networks for Biometric Authentication

“…For each individual, 12 representations of the left hand have been captured, during four different session: under normal condition (Normal); after carrying a 3 kg bag, for one minute (Bag); after squeezing an elastic ball for one minute (Activity) and after cooling the hand in ice (Ice). For each session three images have been taken, with the intension of simulating the physical stress conditions that could appear in real-life situations [21].…”

Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization

“…Some multimodal biometric systems capture palmprint/finger vein [16,17] like shown Fig. 1, hand geometry/vein [18,19]. Other systems capture the palmar veins [20,21] Based on registering finger vein information [22], and it is discriminated of which finger the finger vein information is to be registered, on the basis of the photographed image.…”