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

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet


  • 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.

TitelIECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
Anzahl der Seiten6
VerlagIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)978-1-6654-8026-0
ISBN (elektronisch)978-1-6654-8025-3
PublikationsstatusErschienen - 17.10.2022
VeranstaltungConference - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Convention Center SQUARE, Brussels, Belgien
Dauer: 17.10.202220.10.2022
Konferenznummer: 48

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