Please use this identifier to cite or link to this item:
Title: Palm Vein Recognition using Local Tetra Patterns
Authors: ManMohan
Saxena, Jai
Teckchandani, Kapish
Pandey, Prithu
Dutta, Malay Kishore
Travieso, Carlos M. 
Alonso-Hernandez, Jesus B. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Palm Vein
Local Tetra Patterns (Ltrp)
Contrast Limited Adaptive Histogram Equalization (Clahe)
Cosine Similarity Measure
Put Vein Database
Issue Date: 2015
Journal: 2015 4Th International Work Conference On Bioinspired Intelligence (Iwobi)
Conference: 2015 4th International Work Conference on Bioinspired Intelligence (IWOBI) 
Abstract: Palm Vein Recognition is an emerging touch-less and spoof-resistant means of biometric authentication. However, matching algorithms tend to lack accuracy, due to the complexity of vascular patterns and irregularities in subsequent samples of the same person. This paper proposes a method that describes the spatial structure of local texture using direction of central gray pixel, formulating a discrete set of features which generates a unique template that improves the accuracy of identification. The features from various samples pertaining to the same person are strategically combined. This creates a robust feature vector which is able to handle the irregularities encountered while acquiring images for the database, and improves the efficiency manifolds as compared to present techniques. Matching and score calculation was done using cosine similarity measure. The method was tested on the PUT Vein Database which contained 1200 samples. The results showed an Equal Error Rate of 0%
Source: 2015 4Th International Work Conference On Bioinspired Intelligence (Iwobi), p. 151-155, (2015)
Appears in Collections:Actas de congresos
Show full item record


checked on Sep 20, 2020

Page view(s)

checked on Sep 20, 2020

Google ScholarTM



Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.