A Novel Biometric Identification Approach Based on Human Hand

Author(s):  
Jun Kong ◽  
Miao Qi ◽  
Yinghua Lu ◽  
Shuhua Wang ◽  
Yuru Wang
Sensors ◽  
2012 ◽  
Vol 12 (1) ◽  
pp. 987-1001 ◽  
Author(s):  
Carlos M. Travieso ◽  
Juan Carlos Briceño ◽  
Jesús B. Alonso

2017 ◽  
Vol 17 (2) ◽  
pp. 38-43
Author(s):  
V. Kumar ◽  
A. Dua ◽  
H. Bansal ◽  
H. Aggarwal ◽  
A. Madan ◽  
...  

AbstractPresent manuscript deals with the biometric identification and security. Features exploited for the purpose are the principal lines of the palm of an individual. We developed an algorithm which extracts palm region from a human hand, calculates few palm specific parameters using only principal lines that differentiate one palm from another and then verifies it against a database which contain s the palms of the registered users.


2020 ◽  
Vol 49 (1) ◽  
pp. 55-79
Author(s):  
Jerry Moravec

A biometric identification of persons wchich utilize contour of a human hand belogs to still very interesting and still not totally explored areas and its accuracy and effectiveness depends on technical capabilities to some extent. Presented paper solves given problem using combination of different algorithms. A hand contour is used, topological description of the hand, evolutionary algorithm, algorithm linear regression to estimate the knuckles positions and for contours comparison is used an algorithm Iterative Closest Point (ICP) in its genuine shape. All 5 fingers is at computer classification fully moveable, thumb has 2 knuckles. Modern evolutionary optimizers enable markedly to cut down computational demands of the algorithm ICP. Experimental verification of proposed recipes were performed with use of two different databases named THID and GPDS with persons of both gender and different age (cca 20-65let) with total number of oeprons in individual database 104 and 94. Experimental results checked succesfuly suitability of use combination of methods ICP and evolutionary optimizer which is named as EPSDE for solving of the given task with algorithmic complexity O(N) and success rate give by coefficient THID:EER=0.38% and GPDS:EER=0.35% on real images.


1976 ◽  
Author(s):  
C. W. Suggs ◽  
John Wayne Mishoe

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