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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References
Balkenius, C., Kopp, L.: Robust Self-Localization Using Elastic Templates. In: Lindberg, T. (ed.) Proceedings of Swedish Symposium on Image Analysis (1997)
Chatila, R.: Deliberation and Reactivity in Autonomous Mobile Robots. Robotics and Autonomous Systems 16, 197–211 (1995)
DeSouza, G.N., Kak, A.C.: Vision for Mobile Robot Navigation: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(2), 237–267 (2002)
Fox, D.: Markov Localization: A Probabilistic Framework for Mobile Robot Localization and Navigdation, Ph. D. Thesis, University of Bonn, Germany (December 1998)
Fukunaga, K.: Introduction to statistical pattern recognition. Academic Press, Boston (1990)
Graña, M., Gallego, J.: Associative Mophological Memories for endmember induction. In: Proc. IGARSS 2003, Tolouse, France
Graña, M., Sussner, P., Ritter, G.: Associative Morphological Memories for Endmember Determination in Spectral Unmixing. In: Proc. FUZZ-IEEE (2003)
Graña, M., d’Anjou, A.: Feature Extraction by Linear Spectral Unmixing. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds.) KES 2004. LNCS (LNAI), vol. 3213, pp. 692–697. Springer, Heidelberg (2004)
Graña, M., d’Anjou, A., Albizuri, X.: Morphological memories for feature extraction in hyperspectral images. In: Verleysen, M. (ed.) ESANN 2005, pp. 497–502. dFacto press (2005)
Gross, H.M., Koening, A., Boehme, H.J., Schroeter, C.: Vision-based Monte Carlo Self-localization for a Mobile Service Robot Acting as Shopping Assistant in a Home Store. In: Proceedings of the IEEE Intl. Conference on Intelligent Robots and Systems (2002)
Hopfield, J.J.: Neural networks and physical systems with emergent collective computational abilities. Proc. Nat. Acad. Sciences 79, 2554–2558 (1982)
Keshava, N., Mustard, J.F.: Spectral unimixing. IEEE Signal Proc. Mag. 19(1), 44–57 (2002)
Livatino, S., Madsen, C.: Optimization of Robot Self-Localization Accuracy by Automatic Visual-Landmark Selection. In: Proceedings of 11th Scabdinavian Conference on Image Analysis (SCIA), pp. 501–506 (1999)
Livatino, S., Madsen, C.: Autonomous Robot Navigation with Automatic Learning of Visual Landmarks. In: International Symposium of Intelligent Robotic Systems, SIRSÕ 1999 (1999)
Manolakis, D., Shaw, G.: Detection algorithms for hyperspectral imaging applications. IEEE Signal Proc. Mag. 19(1), 29–43 (2002)
Marando, F., Piaggio, M., Scalzo, A.: Real Time Self Localization Using a Single Frontal Camera. In: International Symposium of Intelligent Robotic Systems, SIRSÕ 2001 (2001)
Ohya, A., Kosaka, A., Kak, A.C.: Vision-Based Navigation by a Mobile Robot with Obstacle Avoidance Using Single-Camera Vision and Ultrasonic Sensing. IEEE Journal of Robotics and Automation 14(6), 969–978 (1998)
Olson, C.F.: Landmark Selection for Terrain Matching. In: Proceedings ICRA 2000 (2000)
Raducanu, B., Graa, M., Sussner, P.: Morphological Neural Networks for vision based self-localization. In: Proc. ICRA 2001
Raducanu, B., Graa, M., Sussner, P.: Steps towards one-shot vision-based self-localization. In: Duro, R., Santos, J., Graa, M. (eds.) Biologically inspired robot behavior engineering, pp. 265–294. Springer, Heidelberg (2002)
Raducanu, B., Graña, M., Albizuri, X.: Morphological scale spaces and associative morphological memories: results on robustness and practical applications. J. Math. Imaging and Vision 19(2), 113–122 (2003)
Reuter, J.: Mobile Robot Self-Localization Using PDAB. In: Proceedings of International Conference on Robotics and Automation, ICRA (2000)
Ritter, G.X., Diaz-de-Leon, J.L., Sussner, P.: Morphological bidirectional associative memories. Neural Networks 12, 851–867 (1999)
Ritter, G.X., Sussner, P., Diaz-de-Leon, J.L.: Morphological associative memories. IEEE Trans. on Neural Networks 9(2), 281–292 (1998)
Ritter, G.X., Urcid, G., Iancu, L.: Reconstruction of patterns from moisy inputs using morphological associative memories. J. Math. Imaging and Vision 19(2), 95–112 (2003)
Ritter, G.X., Urcid, G.: Lattice algebra approach to single-neuron computation. IEEE Trans Neural Networks 14(2), 282–295 (2003)
Rizzi, A., Duina, D., Inelli, S., Cassinis, R.: Unsupervised Matching of Visual Landmarks for Robotic Homing using Fourier-Mellin Transform. Robotics and Autonomous Systems 40, 131–138 (2002)
Saffiotti, A., Wesley, L.P.: Perception-Based Self-Localization Using Fuzzy Location. In: Dorst, L., Voorbraak, F., van Lambalgen, M. (eds.) RUR 1995. LNCS, vol. 1093, pp. 368–385. Springer, Heidelberg (1996)
Sekimori, D., Usui, T., Masutani, Y., Miyazaki, F.: High-Speed Obstacle Avoidance and Self-Localization for Mobile Robots Based on Omni-Directional Imaging of Floor Region. IPSJ Transactions on Computer Vision and Image Media, 42 NoSIG13-012 (2002)
Sussner, P.: Observations on Morphological Associative Memories and the Kernel Method. In: Proc. IJCNN 2001, Washington DC (July 2001)
Sussner, P.: Generalizing operations of binary autoassociative morphological memories using fuzzy set theory. J. Math. Imaging and Vision 19(2), 81–94 (2003)
Villaverde, I., Ibañez, S., Albizuri, F.X., Graña, M.: Morphological neural networks for real-time vision based self-localization. In: Abrham, A., Dote, Y., Furuhashi, T., Köpen, M., Ohuchi, A., Ohsawa, Y. (eds.) Soft Computing as transdisciplinary Science and Techonology, Proc. WSTST 2005. Advances in Soft Computing, pp. 70–79. Springer, Heidelberg (2005)
Villaverde, I., Graña, M., D’Anjou, A.: Morphological Neural Networks for Localization and Mapping. In: Proceedings of the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA 2006), La Coruña (Spain), July 12-14 (2006) (On Print)
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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
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