Material Classification Based on Multi-Spectral NIR Band Image

Dong Keun Han; Jeong Won Ha; Jong Ok Kim

doi:10.1109/ITC-CSCC55581.2022.9894969

Material Classification Based on Multi-Spectral NIR Band Image

Dong Keun Han, Jeong Won Ha, Jong Ok Kim

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

In this paper, we study the usefulness of multi-spectral NIR band images instead of RGB only for material classification. To effectively learn a target material, the proposed method uses multi-spectral NIR bands which provide more information than a single NIR band. A new NIR multi-band dataset was built using the hyperspectral camera. As a result, we can find a meaningful correlation with NIR multi bands, and effectively classify the surface material of an object.

Original language	English
Title of host publication	ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	940-942
Number of pages	3
ISBN (Electronic)	9781665485593
DOIs	https://doi.org/10.1109/ITC-CSCC55581.2022.9894969
Publication status	Published - 2022
Event	37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 - Phuket, Thailand Duration: 2022 Jul 5 → 2022 Jul 8

Publication series

Name	ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications

Conference

Conference	37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022
Country/Territory	Thailand
City	Phuket
Period	22/7/5 → 22/7/8

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A4A4079705) and in part by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2020-0-01749) supervised by the IITP(Institute of Information & Communications Technology Planning & Evaluation).

Publisher Copyright:
© 2022 IEEE.

Keywords

material classification
Multi-spectral band
near-infrared (NIR)
surface material

ASJC Scopus subject areas

Information Systems
Electrical and Electronic Engineering
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Hardware and Architecture

Access to Document

10.1109/ITC-CSCC55581.2022.9894969

Cite this

Han, D. K., Ha, J. W., & Kim, J. O. (2022). Material Classification Based on Multi-Spectral NIR Band Image. In ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications (pp. 940-942). (ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITC-CSCC55581.2022.9894969

Material Classification Based on Multi-Spectral NIR Band Image. / Han, Dong Keun; Ha, Jeong Won; Kim, Jong Ok.
ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications. Institute of Electrical and Electronics Engineers Inc., 2022. p. 940-942 (ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Han, DK, Ha, JW & Kim, JO 2022, Material Classification Based on Multi-Spectral NIR Band Image. in ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications. ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications, Institute of Electrical and Electronics Engineers Inc., pp. 940-942, 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022, Phuket, Thailand, 22/7/5. https://doi.org/10.1109/ITC-CSCC55581.2022.9894969

Han DK, Ha JW, Kim JO. Material Classification Based on Multi-Spectral NIR Band Image. In ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications. Institute of Electrical and Electronics Engineers Inc. 2022. p. 940-942. (ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications). doi: 10.1109/ITC-CSCC55581.2022.9894969

Han, Dong Keun ; Ha, Jeong Won ; Kim, Jong Ok. / Material Classification Based on Multi-Spectral NIR Band Image. ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 940-942 (ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications).

@inproceedings{e202d6f5e1504ba89df25fe2f2a6d5c0,

title = "Material Classification Based on Multi-Spectral NIR Band Image",

abstract = "In this paper, we study the usefulness of multi-spectral NIR band images instead of RGB only for material classification. To effectively learn a target material, the proposed method uses multi-spectral NIR bands which provide more information than a single NIR band. A new NIR multi-band dataset was built using the hyperspectral camera. As a result, we can find a meaningful correlation with NIR multi bands, and effectively classify the surface material of an object.",

keywords = "material classification, Multi-spectral band, near-infrared (NIR), surface material",

author = "Han, {Dong Keun} and Ha, {Jeong Won} and Kim, {Jong Ok}",

note = "Funding Information: This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A4A4079705) and in part by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2020-0-01749) supervised by the IITP(Institute of Information & Communications Technology Planning & Evaluation). Publisher Copyright: {\textcopyright} 2022 IEEE.; 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 ; Conference date: 05-07-2022 Through 08-07-2022",

year = "2022",

doi = "10.1109/ITC-CSCC55581.2022.9894969",

language = "English",

series = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "940--942",

booktitle = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",

}

TY - GEN

T1 - Material Classification Based on Multi-Spectral NIR Band Image

AU - Han, Dong Keun

AU - Ha, Jeong Won

AU - Kim, Jong Ok

N1 - Funding Information: This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A4A4079705) and in part by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2020-0-01749) supervised by the IITP(Institute of Information & Communications Technology Planning & Evaluation). Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - In this paper, we study the usefulness of multi-spectral NIR band images instead of RGB only for material classification. To effectively learn a target material, the proposed method uses multi-spectral NIR bands which provide more information than a single NIR band. A new NIR multi-band dataset was built using the hyperspectral camera. As a result, we can find a meaningful correlation with NIR multi bands, and effectively classify the surface material of an object.

AB - In this paper, we study the usefulness of multi-spectral NIR band images instead of RGB only for material classification. To effectively learn a target material, the proposed method uses multi-spectral NIR bands which provide more information than a single NIR band. A new NIR multi-band dataset was built using the hyperspectral camera. As a result, we can find a meaningful correlation with NIR multi bands, and effectively classify the surface material of an object.

KW - material classification

KW - Multi-spectral band

KW - near-infrared (NIR)

KW - surface material

UR - http://www.scopus.com/inward/record.url?scp=85140652635&partnerID=8YFLogxK

U2 - 10.1109/ITC-CSCC55581.2022.9894969

DO - 10.1109/ITC-CSCC55581.2022.9894969

M3 - Conference contribution

AN - SCOPUS:85140652635

T3 - ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications

SP - 940

EP - 942

BT - ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022

Y2 - 5 July 2022 through 8 July 2022

ER -

Material Classification Based on Multi-Spectral NIR Band Image

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this