Using Simple Genetic Algorithm for a Hand Contour Classification: An Experimental Study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F20%3A39916054" target="_blank" >RIV/00216275:25530/20:39916054 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-51971-1_8" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-51971-1_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-51971-1_8" target="_blank" >10.1007/978-3-030-51971-1_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using Simple Genetic Algorithm for a Hand Contour Classification: An Experimental Study

Popis výsledku v původním jazyce

The area of biometric systems has passed through considerable advancement in the past two decades. Supporting of security provision plays a key role in many branches. There are large amount of the biometrical markers which can be utilized in the person identification process. One of the possible ways is a method which uses a hand shape contour classification. The presented paper solves the problem of hand contours classification with use of a Simple Genetic Algorithm (SGA). The foundations of the SGA were established in 1950’s, but an improvement process of the SGA continues. The hand contour for the classification purposes is obtained from a color image from a biometric scanner. The biometric scanner has fixed pegs to hold the hand, or the hand can be freely placed on the scanning area. A core of the proposed estimator is an Iterative Closes Point algorithm which enables matching of the two point-clouds and expressing their dissimilarity regarding the elected metrics. In the experimental section, a large number of experiments were performed with a different setting of the SGA working parameters. Beside the capability to correctly align/match the hand contours, selected standard benchmark tests were performed with a corresponding number of dimensions. The presented estimator solves the thee-dimensional optimization task. Based on experimental results, it was proven that in the case of identical contours the proposed method, which utilizes the SGA optimizer, provides very accurate results.

Název v anglickém jazyce

Using Simple Genetic Algorithm for a Hand Contour Classification: An Experimental Study

Popis výsledku anglicky

The area of biometric systems has passed through considerable advancement in the past two decades. Supporting of security provision plays a key role in many branches. There are large amount of the biometrical markers which can be utilized in the person identification process. One of the possible ways is a method which uses a hand shape contour classification. The presented paper solves the problem of hand contours classification with use of a Simple Genetic Algorithm (SGA). The foundations of the SGA were established in 1950’s, but an improvement process of the SGA continues. The hand contour for the classification purposes is obtained from a color image from a biometric scanner. The biometric scanner has fixed pegs to hold the hand, or the hand can be freely placed on the scanning area. A core of the proposed estimator is an Iterative Closes Point algorithm which enables matching of the two point-clouds and expressing their dissimilarity regarding the elected metrics. In the experimental section, a large number of experiments were performed with a different setting of the SGA working parameters. Beside the capability to correctly align/match the hand contours, selected standard benchmark tests were performed with a corresponding number of dimensions. The presented estimator solves the thee-dimensional optimization task. Based on experimental results, it was proven that in the case of identical contours the proposed method, which utilizes the SGA optimizer, provides very accurate results.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Artificial Intelligence and Bioinspired Computational Methods : Proceedings of the 9th Computer Science On-line Conference 2020, Vol. 2

ISBN

978-3-030-51970-4

ISSN

—

e-ISSN

—

Počet stran výsledku

16

Strana od-do

93-109

Název nakladatele

Springer Nature Switzerland AG

Místo vydání

Cham

Místo konání akce

online

Datum konání akce

23. 4. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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