Hand-Dorsa Vein Recognition Based on Coded and Weighted Partition Local Binary Patterns

2011 ◽  
Author(s):  
Yiding Wang ◽  
Kefeng Li ◽  
L. Shark ◽  
M. R. Varley
Keyword(s):  
Local Binary Patterns ◽  
Vein Recognition ◽  
Weighted Partition

scholarly journals Finger Vein Recognition with Gabor Wavelets and Local Binary Patterns

2013 ◽  
Vol E96.D (8) ◽  
pp. 1886-1889 ◽  
Author(s):  
Jialiang PENG ◽  
Qiong LI ◽  
Ahmed A. ABD EL-LATIF ◽  
Ning WANG ◽  
Xiamu NIU
Keyword(s):  
Local Binary Patterns ◽  
Gabor Wavelets ◽  
Finger Vein ◽  
Vein Recognition ◽  
Finger Vein Recognition

Hand-dorsa Vein Recognition Based on Improved Partition Local Binary Patterns

2015 ◽  
pp. 312-320 ◽  
Author(s):  
Kefeng Li ◽  
Guangyuan Zhang ◽  
Yiding Wang ◽  
Peng Wang ◽  
Cui Ni
Keyword(s):  
Local Binary Patterns ◽  
Vein Recognition

IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

2018 ◽  
Vol 1 (2) ◽  
pp. 34-44
Author(s):  
Faris E Mohammed ◽  
Dr. Eman M ALdaidamony ◽  
Prof. A. M Raid
Keyword(s):  
Iris Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Individual Identification ◽  
Work Place ◽  
Identification Process ◽  
Finger Vein ◽  
Noise Point ◽  
Vein Recognition ◽  
A New Technique

Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new technique named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of tremendous key-point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and improvement steps are critical for SIFT-based recognition for iris and finger vein , and the proposed technique can accomplish satisfactory recognition performance. Keywords: SIFT, Iris Recognition, Finger Vein identification and Biometric Systems.   © 2018 JASET, International Scholars and Researchers Association    

Local Binary Patterns with ENI features for Images classification and analysis

2011 ◽  
Vol 2 (1) ◽  
pp. 45-50
Author(s):  
E. Suresh Babu ◽  
S. Salma ◽  
A. Reshma ◽  
C. Nagaraju
Keyword(s):  
Local Binary Patterns
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