loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ulrich Kaufmann 1 ; Roland Reichle 2 ; Christof Hoppe 2 and Philipp A. Baer 2

Affiliations: 1 Institute of Neural Information Processing, University of Ulm, Germany ; 2 Distributed Systems Group, University of Kassel, Germany

Abstract: One of the key requirements of robotic vision systems for real-life application is the ability to deal with varying lighting conditions. Many systems rely on color-based object or feature detection using color segmentation. A static approach based on preinitialized calibration data is not likely to perform very well under natural light. In this paper we present an unsupervised approach for color segmentation which is able to self-adapt to varying lighting conditions during run-time. The approach comprises two steps: initialization and iterative tracking of color regions. Its applicability has been tested on vision systems of soccer robots participating in RoboCup tournaments.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.216.104.106

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Kaufmann, U.; Reichle, R.; Hoppe, C. and A. Baer, P. (2007). An Unsupervised Approach for Adaptive Color Segmentation. In Robot Vision (VISAPP 2007) - Robot Vision; ISBN 978-972-8865-76-4, SciTePress, pages 3-12. DOI: 10.5220/0002066200030012

@conference{robot vision07,
author={Ulrich Kaufmann. and Roland Reichle. and Christof Hoppe. and Philipp {A. Baer}.},
title={An Unsupervised Approach for Adaptive Color Segmentation},
booktitle={Robot Vision (VISAPP 2007) - Robot Vision},
year={2007},
pages={3-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002066200030012},
isbn={978-972-8865-76-4},
}

TY - CONF

JO - Robot Vision (VISAPP 2007) - Robot Vision
TI - An Unsupervised Approach for Adaptive Color Segmentation
SN - 978-972-8865-76-4
AU - Kaufmann, U.
AU - Reichle, R.
AU - Hoppe, C.
AU - A. Baer, P.
PY - 2007
SP - 3
EP - 12
DO - 10.5220/0002066200030012
PB - SciTePress