Thermal-based gender recognition using drones: advancing biometric recognition in challenging outdoor environments

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F24%3A39921878" target="_blank" >RIV/00216275:25410/24:39921878 - isvavai.cz</a>

Result on the web

<a href="https://cdnsciencepub.com/doi/10.1139/dsa-2023-0075" target="_blank" >https://cdnsciencepub.com/doi/10.1139/dsa-2023-0075</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1139/dsa-2023-0075" target="_blank" >10.1139/dsa-2023-0075</a>

Result language

angličtina

Original language name

Thermal-based gender recognition using drones: advancing biometric recognition in challenging outdoor environments

Original language description

While biometric recognition typically uses features such as face, fingerprint, and iris to identify individuals, this study focuses on utilising specific characteristics to identify gender. The aim of this article is to propose a procedure for gender recognition under specific conditions. The specific condition addressed is outdoor area monitoring, which presents challenges such as varying lighting conditions and limited camera placement options. To tackle this, a proposed procedure utilises thermal images captured by the drone equipped with a thermal camera. The advantage of thermal images is their independence from ambient light conditions. The captured images are resized and processed using convolutional neural networks (CNNs) (AlexNet, VGG-16, VGG-19) for feature extraction and binary classification. A freely available database of thermal face images is used for training the CNNs, while a own created dataset of thermal images obtained by the drone is used for testing. The findings indicate that the optimised CNNs achieve classification accuracies of 82.4% (VGG-16), 82.9% (AlexNet), and 85.5% (VGG-19). The original contribution of this study lies in demonstrating the suitability of face thermal images obtained through drones for gender recognition purposes.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

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

Name of the periodical

Drone Systems and Applications

ISSN

2564-4939

e-ISSN

2564-4939

Volume of the periodical

12

Issue of the periodical within the volume

January

Country of publishing house

CA - CANADA

Number of pages

9

Pages from-to

1-9

UT code for WoS article

001264010100001

EID of the result in the Scopus database

2-s2.0-85199621964