3D Ultrasound palm vein pattern for biometric recognition

2012 ◽  
Author(s):  
Antonio Iula ◽  
Alessandro Savoia ◽  
Giosue Caliano
Keyword(s):  
3D Ultrasound ◽  
Biometric Recognition ◽  
Vein Pattern ◽  
Palm Vein

Palm vein pattern-based biometric recognition system

2015 ◽  
Vol 51 (2) ◽  
pp. 105 ◽  
Author(s):  
Gunjan Shah ◽  
Sagar Shirke ◽  
Sonam Sawant ◽  
Yogesh H. Dandawate
Keyword(s):  
Recognition System ◽  
Biometric Recognition ◽  
Vein Pattern ◽  
Palm Vein

Palm Vein Recognition Based on Independent Component Analysis

2013 ◽  
Vol 333-335 ◽  
pp. 1106-1109
Author(s):  
Wei Wu
Keyword(s):  
Pattern Recognition ◽  
Independent Component Analysis ◽  
Euclidean Distance ◽  
Recognition Performance ◽  
Component Analysis ◽  
Independent Component ◽  
Experimental Results ◽  
Vein Pattern ◽  
Vein Recognition ◽  
Palm Vein

Palm vein pattern recognition is one of the newest biometric techniques researched today. This paper proposes project the palm vein image matrix based on independent component analysis directly, then calculates the Euclidean distance of the projection matrix, seeks the nearest distance for classification. The experiment has been done in a self-build palm vein database. Experimental results show that the algorithm of independent component analysis is suitable for palm vein recognition and the recognition performance is practical.

A New Location Method of ROI for Contactless Palm Vein Recognition

2013 ◽  
Vol 760-762 ◽  
pp. 1398-1401
Author(s):  
Wei Wu ◽  
Wei Qi Yuan ◽  
Hui Song
Keyword(s):  
Pattern Recognition ◽  
Recognition Rate ◽  
New Method ◽  
Vein Pattern ◽  
Location Method ◽  
Vein Recognition ◽  
Palm Vein ◽  
New Location

Palm vein pattern recognition is one of the newest biometric techniques researched today.At present, literatures selecte the center of the palm as the ROI of palm vein recognition. However the vein image in this area is not clear in some peoples palm. In this paper, we proposed a new location method of ROI which takes thenar area as the ROI. In the experiment part, it compares the recognition rate between the new and the traditional ROI in self-established contactless palm vein database. The result shows that this new method has got the recognition rate of 98.9258% and has increased recognition rate 2.0911% compared with the traditional one.

A hybrid fusion model of iris, palm vein and finger vein for multi-biometric recognition system

2020 ◽  
Vol 79 (39-40) ◽  
pp. 29021-29042
Author(s):  
Chenyi Zhou ◽  
Jing Huang ◽  
Feng Yang ◽  
Yaqin Liu
Keyword(s):  
Recognition System ◽  
Fusion Model ◽  
Biometric Recognition ◽  
Finger Vein ◽  
Palm Vein ◽  
Hybrid Fusion

scholarly journals Palm Vein Verification Using Multiple Features and Locality Preserving Projections

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Ali Mohsin Al-juboori ◽  
Wei Bu ◽  
Xiangqian Wu ◽  
Qiushi Zhao
Keyword(s):  
Extraction Methods ◽  
Physiological Characteristic ◽  
Experimental Result ◽  
Filter Method ◽  
Vein Pattern ◽  
Locality Preserving Projections ◽  
Locality Preserving ◽  
Feature Based ◽  
Commercial Applications ◽  
Palm Vein

Biometrics is defined as identifying people by their physiological characteristic, such as iris pattern, fingerprint, and face, or by some aspects of their behavior, such as voice, signature, and gesture. Considerable attention has been drawn on these issues during the last several decades. And many biometric systems for commercial applications have been successfully developed. Recently, the vein pattern biometric becomes increasingly attractive for its uniqueness, stability, and noninvasiveness. A vein pattern is the physical distribution structure of the blood vessels underneath a person’s skin. The palm vein pattern is very ganglion and it shows a huge number of vessels. The attitude of the palm vein vessels stays in the same location for the whole life and its pattern is definitely unique. In our work, the matching filter method is proposed for the palm vein image enhancement. New palm vein features extraction methods, global feature extracted based on wavelet coefficients and locality preserving projections (WLPP), and local feature based on local binary pattern variance and locality preserving projections (LBPV_LPP) have been proposed. Finally, the nearest neighbour matching method has been proposed that verified the test palm vein images. The experimental result shows that the EER to the proposed method is 0.1378%.

Biometric Recognition System Based on Hand Vein Pattern

2009 ◽  
Vol 29 (12) ◽  
pp. 3339-3343 ◽  
Author(s):  
刘铁根 Liu Tiegen ◽  
王云新 Wang Yunxin ◽  
李秀艳 Li Xiuyan Jiang ◽  
江俊峰 Junfeng ◽  
周苏晋 Zhou Sujin
Keyword(s):  
Recognition System ◽  
Biometric Recognition ◽  
Vein Pattern ◽  
Hand Vein

scholarly journals Wrist Vascular Biometric Recognition Using a Portable Contactless System

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1469 ◽  
Author(s):  
Raul Garcia-Martin ◽  
Raul Sanchez-Reillo
Keyword(s):  
Near Infrared ◽  
Computing Time ◽  
Recognition Task ◽  
Biometric Recognition ◽  
Real Time Processing ◽  
Environmental Light ◽  
Best Value ◽  
Contactless System ◽  
Definition Of ◽  
Palm Vein

Human wrist vein biometric recognition is one of the least used vascular biometric modalities. Nevertheless, it has similar usability and is as safe as the two most common vascular variants in the commercial and research worlds: hand palm vein and finger vein modalities. Besides, the wrist vein variant, with wider veins, provides a clearer and better visualization and definition of the unique vein patterns. In this paper, a novel vein wrist non-contact system has been designed, implemented, and tested. For this purpose, a new contactless database has been collected with the software algorithm TGS-CVBR®. The database, called UC3M-CV1, consists of 1200 near-infrared contactless images of 100 different users, collected in two separate sessions, from the wrists of 50 subjects (25 females and 25 males). Environmental light conditions for the different subjects and sessions have been not controlled: different daytimes and different places (outdoor/indoor). The software algorithm created for the recognition task is PIS-CVBR®. The results obtained by combining these three elements, TGS-CVBR®, PIS-CVBR®, and UC3M-CV1 dataset, are compared using two other different wrist contact databases, PUT and UC3M (best value of Equal Error Rate (EER) = 0.08%), taken into account and measured the computing time, demonstrating the viability of obtaining a contactless real-time-processing wrist system.

Sign in / Sign up

Export Citation Format

Share Document