IMAGE SEGMENTATION FOR OBJECT DETECTION ON A DEEPLY EMBEDDED MINIATURE ROBOT

Alexander Jungmann, Thomas Schierbaum, Bernd Kleinjohann

Abstract

In this paper, an image segmentation approach for object detection on the miniature robot BeBot - a deeply embedded system - is presented. In order to enable the robot to detect and identify objects in its environment by means of its camera, an efficient image segmentation approach was developed. The fundamental algorithm bases on the region growing and region merging concept and identifies homogeneous regions consisting of adjacent pixels with similar color. By internally representing a contiguous block of pixels in terms of runlengths, the computational effort of both the region growing and the region merging operation is minimized. Finally, for subsequent object detection processes, a region is efficiently translated into a statistically feature representation based on discretized moments.

References

  1. Herbrechtsmeier, S., Witkowski, U., and RĂ¼ ckert, U. (2009). Bebot: A modular mobile miniature robot platform supporting hardware reconfiguration and multi-standard communication. In Progress in Robotics, volume 44, pages 346-356. Springer Berlin Heidelberg.
  2. Hu, M.-K. (1962). Visual pattern recognition by moment invariants. Information Theory, IEEE Transactions on, 8(2):179-187.
  3. Prokop, R. J. and Reeves, A. P. (1992). A survey of moment-based techniques for unoccluded object representation and recognition. CVGIP: Graph. Models Image Process., 54(5):438-460.
  4. Teague, M. R. (1980). Image analysis via the general theory of moments. Journal of the Optical Society of America (1917-1983), 70:920-930.
  5. Zakaria, M. F., Vroomen, L. J., Zsombor-Murray, P. J. A., and van Kessel, J. M. H. M. (1987). Fast algorithm for the computation of moment invariants. Pattern Recogn., 20(6):639-643.
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Paper Citation


in Harvard Style

Jungmann A., Schierbaum T. and Kleinjohann B. (2012). IMAGE SEGMENTATION FOR OBJECT DETECTION ON A DEEPLY EMBEDDED MINIATURE ROBOT . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 441-444. DOI: 10.5220/0003852104410444


in Bibtex Style

@conference{visapp12,
author={Alexander Jungmann and Thomas Schierbaum and Bernd Kleinjohann},
title={IMAGE SEGMENTATION FOR OBJECT DETECTION ON A DEEPLY EMBEDDED MINIATURE ROBOT},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={441-444},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003852104410444},
isbn={978-989-8565-03-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - IMAGE SEGMENTATION FOR OBJECT DETECTION ON A DEEPLY EMBEDDED MINIATURE ROBOT
SN - 978-989-8565-03-7
AU - Jungmann A.
AU - Schierbaum T.
AU - Kleinjohann B.
PY - 2012
SP - 441
EP - 444
DO - 10.5220/0003852104410444