A Hand Contour Classification Using Ensemble of Natural Features: A Large Comparative Study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F20%3A39916053" target="_blank" >RIV/00216275:25530/20:39916053 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-51971-1_3" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-51971-1_3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-51971-1_3" target="_blank" >10.1007/978-3-030-51971-1_3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Hand Contour Classification Using Ensemble of Natural Features: A Large Comparative Study

Popis výsledku v původním jazyce

Biometrics is a standalone scientific discipline which enjoys more and more attention of many researchers. The provision of the general security plays a key role in many modern branches. In the presented paper a person identification task is solved using the shape of a human hand, and also the hand contour classification algorithm based on an evolutionary estimator is also. The proposed methodology provides the comparison of the identified person with a set of model contours. The examination of the proposed method was performed with use of a database which contains 940 images of the scanned hands from 94 persons, including 10 images from every person. Totally 88360 combinations of the input images. The proposed evolutionary estimator uses an EPSDE algorithm, which is derived from a differential evolution algorithm which was proposed at the end of the 90’s. The model of the hand contour of every person is represented by only one image, which has movable finger contours in the classification process regarding the knuckle positions of the hand. Thanks to that, it is not necessary to use the pegs to hold the individual fingers in correct positions. The hand can be both placed on a support desk or can be freely hung in the air. All results obtained at classification time with use of the presented evolutionary estimator provide accuracy of approximately 98%.

Název v anglickém jazyce

A Hand Contour Classification Using Ensemble of Natural Features: A Large Comparative Study

Popis výsledku anglicky

Biometrics is a standalone scientific discipline which enjoys more and more attention of many researchers. The provision of the general security plays a key role in many modern branches. In the presented paper a person identification task is solved using the shape of a human hand, and also the hand contour classification algorithm based on an evolutionary estimator is also. The proposed methodology provides the comparison of the identified person with a set of model contours. The examination of the proposed method was performed with use of a database which contains 940 images of the scanned hands from 94 persons, including 10 images from every person. Totally 88360 combinations of the input images. The proposed evolutionary estimator uses an EPSDE algorithm, which is derived from a differential evolution algorithm which was proposed at the end of the 90’s. The model of the hand contour of every person is represented by only one image, which has movable finger contours in the classification process regarding the knuckle positions of the hand. Thanks to that, it is not necessary to use the pegs to hold the individual fingers in correct positions. The hand can be both placed on a support desk or can be freely hung in the air. All results obtained at classification time with use of the presented evolutionary estimator provide accuracy of approximately 98%.

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

19

Strana od-do

26-45

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

—