A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

  • Oscar Real-Moreno
  • Julio C. Rodriguez-Quinonez
  • Oleg Sergiyenko
  • Wendy Flores-Fuentes
  • Moises J. Castro-Toscano
  • Jesus E. Miranda-Vega
  • Paolo Mercorelli
  • Jorge Alejandro Valdez-Rodriguez
  • Gabriel Trujillo-Hernandez
  • Jonathan J. Sanchez-Castro

Stereo vision systems are well know depth estimation methods with a large number of applications such as automatic inspection, autonomous navigation, process control, etc. The functioning principle of these systems is the triangulation between the real-world surface point and its respective projections on the image planes of each camera. One of the key points in order to obtain accurate measurements on stereo vision systems are the calibration of extrinsic and intrinsic parameters. This is why the work of this paper focuses on a camera calibration method to correct the error generated by the lens distortion. The proposed method divides the image in quadrants and generates an equation for each quadrant to correct the error generated by the lens distortion. The performed experiment demonstrated an accuracy improvement using the calibration method compared to the measures taken without a calibration method.

Original languageEnglish
Title of host publicationIECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
Number of pages6
Place of PublicationPiscataway
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date17.10.2022
ISBN (print)978-1-6654-8026-0
ISBN (electronic)978-1-6654-8025-3
DOIs
Publication statusPublished - 17.10.2022
EventConference - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Convention Center SQUARE, Brussels, Belgium
Duration: 17.10.202220.10.2022
Conference number: 48
https://iecon2022.org

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

    Research areas

  • depth estimation, Lens distortion, pattern match, Stereo vision system, triangulation
  • Engineering

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