A Geometric Edge Detection Method from Cross-sectional Shapes of Cloth-like Object

Ibuki Yamamoto, Takashi Yoshimi, Motoki Hirayama

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

Abstract

This study aims to propose methods that detect edge of the cloth by using a displacement laser sensor for the automatic sawing by a robot arm. For the edge detection, three filters which extract candidates are used, then the most suitable point is selected by the proposed condition. We tested the method at the required feeding speeds under moving the cloth with some feeding speeds. Then, we confirmed that the proposed method can detect whole edge in all cases.

Original languageEnglish
Title of host publicationICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings
PublisherIEEE Computer Society
Pages292-295
Number of pages4
ISBN (Electronic)9788993215182
DOIs
Publication statusPublished - 2019 Oct
Event19th International Conference on Control, Automation and Systems, ICCAS 2019 - Jeju, Korea, Republic of
Duration: 2019 Oct 152019 Oct 18

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2019-October
ISSN (Print)1598-7833

Conference

Conference19th International Conference on Control, Automation and Systems, ICCAS 2019
CountryKorea, Republic of
CityJeju
Period19/10/1519/10/18

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Keywords

  • Displacement Laser Sensor
  • Edge Detection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Yamamoto, I., Yoshimi, T., & Hirayama, M. (2019). A Geometric Edge Detection Method from Cross-sectional Shapes of Cloth-like Object. In ICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings (pp. 292-295). [8971697] (International Conference on Control, Automation and Systems; Vol. 2019-October). IEEE Computer Society. https://doi.org/10.23919/ICCAS47443.2019.8971697