Methods for Magnetic Signature Comparison Evaluation in Vehicle Re-Identification Context

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10256132" target="_blank" >RIV/61989100:27240/24:10256132 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2079-9292/13/14/2722" target="_blank" >https://www.mdpi.com/2079-9292/13/14/2722</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/electronics13142722" target="_blank" >10.3390/electronics13142722</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Methods for Magnetic Signature Comparison Evaluation in Vehicle Re-Identification Context

Popis výsledku v původním jazyce

Intelligent transportation systems represent innovative solutions for traffic congestion minimization, mobility improvements and safety enhancement. These systems require various inputs about vehicles and traffic state. Vehicle re-identification systems based on video cameras are most popular; however, more strict privacy policy necessitates depersonalized vehicle re-identification systems. Promising research for depersonalized vehicle re-identification systems involves leveraging the captured unique distortions induced in the Earth&apos;s magnetic field by passing vehicles. Employing anisotropic magneto-resistive sensors embedded in the road surface system captures vehicle magnetic signatures for similarity evaluation. A novel vehicle re-identification algorithm utilizing Euclidean distances and Pearson correlation coefficients is analyzed, and performance is evaluated. Initial processing is applied on registered magnetic signatures, useful features for decision making are extracted, different classification algorithms are applied and prediction accuracy is checked. The results demonstrate the effectiveness of our approach, achieving 97% accuracy in vehicle re-identification for a subset of 300 different vehicles passing the sensor a few times. (C) 2024 by the authors.

Název v anglickém jazyce

Methods for Magnetic Signature Comparison Evaluation in Vehicle Re-Identification Context

Popis výsledku anglicky

Intelligent transportation systems represent innovative solutions for traffic congestion minimization, mobility improvements and safety enhancement. These systems require various inputs about vehicles and traffic state. Vehicle re-identification systems based on video cameras are most popular; however, more strict privacy policy necessitates depersonalized vehicle re-identification systems. Promising research for depersonalized vehicle re-identification systems involves leveraging the captured unique distortions induced in the Earth&apos;s magnetic field by passing vehicles. Employing anisotropic magneto-resistive sensors embedded in the road surface system captures vehicle magnetic signatures for similarity evaluation. A novel vehicle re-identification algorithm utilizing Euclidean distances and Pearson correlation coefficients is analyzed, and performance is evaluated. Initial processing is applied on registered magnetic signatures, useful features for decision making are extracted, different classification algorithms are applied and prediction accuracy is checked. The results demonstrate the effectiveness of our approach, achieving 97% accuracy in vehicle re-identification for a subset of 300 different vehicles passing the sensor a few times. (C) 2024 by the authors.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Electronics

ISSN

2079-9292

e-ISSN

—

Svazek periodika

13

Číslo periodika v rámci svazku

14

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

14

Strana od-do

—

Kód UT WoS článku

001277104100001

EID výsledku v databázi Scopus

2-s2.0-85199629517