Material Classification Based on Multi-Spectral NIR Band Image

Dong Keun Han, Jeong Won Ha, Jong Ok Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (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 languageEnglish
Title of host publicationITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages940-942
Number of pages3
ISBN (Electronic)9781665485593
DOIs
Publication statusPublished - 2022
Event37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 - Phuket, Thailand
Duration: 2022 Jul 52022 Jul 8

Publication series

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

Conference

Conference37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022
Country/TerritoryThailand
CityPhuket
Period22/7/522/7/8

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

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