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International Conference on Artificial Neural Networks

ICANN 2006: Artificial Neural Networks – ICANN 2006 pp 878–887Cite as

Morphological Neural Networks and Vision Based Mobile Robot Navigation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4131))

Abstract

Morphological Associative Memories (MAM) have been proposed for image denoising and pattern recognition. We have shown that they can be applied to other domains, like image retrieval and hyperspectral image unsupervised segmentation. In both cases the key idea is that Morphological Autoassociative Memories (MAAM) selective sensitivity to erosive and dilative noise can be applied to detect the morphological independence between patterns. The convex coordinates obtained by linear unmixing based on the sets of morphological independent patterns define a feature extraction process. These features may be useful either for pattern classification. We present some results on the task of visual landmark recognition for a mobile robot self-localization task.

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Author information

Authors and Affiliations

  1. Dept. CCIA, UPV/EHU, Apdo. 649, 20080, San Sebastian, Spain

    I. Villaverde, M. Graña & A. d’Anjou

Authors
  1. I. Villaverde
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  2. M. Graña
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  3. A. d’Anjou
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Editor information

Editors and Affiliations

  1. School of Electrical and Computer Engineering, Image, Video and Multimedia Systems Laboratory, National Technical University of Athens, GR-157 80, Zographou, Greece

    Stefanos D. Kollias

  2. Department of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zographou, Greece

    Andreas Stafylopatis

  3. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  4. Adaptive Informatics Research Centre, Helsinki University of Technology, HUT, P.O. Box 5400, 02015, Finland

    Erkki Oja

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© 2006 Springer-Verlag Berlin Heidelberg

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Villaverde, I., Graña, M., d’Anjou, A. (2006). Morphological Neural Networks and Vision Based Mobile Robot Navigation. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_91

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  • DOI: https://doi.org/10.1007/11840817_91

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38625-4

  • Online ISBN: 978-3-540-38627-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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