Using hyperspectral imaging to identify optimal narrowband filter parameters for construction and demolition waste classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F25%3A00380458" target="_blank" >RIV/68407700:21110/25:00380458 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/25:00380458

Výsledek na webu

<a href="https://doi.org/10.1016/j.resconrec.2025.108123" target="_blank" >https://doi.org/10.1016/j.resconrec.2025.108123</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.resconrec.2025.108123" target="_blank" >10.1016/j.resconrec.2025.108123</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using hyperspectral imaging to identify optimal narrowband filter parameters for construction and demolition waste classification

Popis výsledku v původním jazyce

Hyperspectral imaging (HSI) is widely applied in various industries, enabling detailed analysis of material properties or composition through their spectral signatures. However, for classification of construction and demolition waste (CDW) materials, HSI is impractical since real-time sorting requires rapid data acquisition and lightweight classification. Instead, fitting selected narrowband filters onto standard cameras can achieve comparable results with substantially reduced computational overhead. In this study, reflectance data of common CDW materials were recorded using a hyperspectral camera, and a multilayer perceptron classifier was employed to evaluate different feature sets. The findings indicate that adding only two wavelengths beyond the RGB channels is sufficient for high-accuracy classification, with optimal filter central wavelengths identified at approximately 650-750 nm and 850-1000 nm across the tested bandwidths (5-50 nm) highlighting the importance of near-infrared regions for material discrimination.

Název v anglickém jazyce

Using hyperspectral imaging to identify optimal narrowband filter parameters for construction and demolition waste classification

Popis výsledku anglicky

Hyperspectral imaging (HSI) is widely applied in various industries, enabling detailed analysis of material properties or composition through their spectral signatures. However, for classification of construction and demolition waste (CDW) materials, HSI is impractical since real-time sorting requires rapid data acquisition and lightweight classification. Instead, fitting selected narrowband filters onto standard cameras can achieve comparable results with substantially reduced computational overhead. In this study, reflectance data of common CDW materials were recorded using a hyperspectral camera, and a multilayer perceptron classifier was employed to evaluate different feature sets. The findings indicate that adding only two wavelengths beyond the RGB channels is sufficient for high-accuracy classification, with optimal filter central wavelengths identified at approximately 650-750 nm and 850-1000 nm across the tested bandwidths (5-50 nm) highlighting the importance of near-infrared regions for material discrimination.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotika a pokročilá průmyslová výroba</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Resources, Conservation and Recycling

ISSN

0921-3449

e-ISSN

1879-0658

Svazek periodika

215

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

001405318500001

EID výsledku v databázi Scopus

2-s2.0-85215085501