@inproceedings{203e3e2716ff44bbb0a6850c14e2d5e7,
title = "Morphological neural networks and vision based mobile robot navigation",
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.",
author = "I. Villaverde and M. Gra{\~n}a and A. D'Anjou",
year = "2006",
doi = "10.1007/11840817\_91",
language = "English",
isbn = "3540386254",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "878--887",
booktitle = "Artificial Neural Networks, ICANN 2006 - 16th International Conference, Proceedings",
address = "Germany",
note = "16th International Conference on Artificial Neural Networks, ICANN 2006 ; Conference date: 10-09-2006 Through 14-09-2006",
}