Innovative applications of associative morphological memories for image processing and pattern recognition

• Autores: Manuel Graña Romay, P. Sussner, G. Ritter
• Localización: Mathware & soft computing: The Magazine of the European Society for Fuzzy Logic and Technology, ISSN-e 1134-5632, Vol. 10, Nº. 3, 2003, págs. 155-168
• Idioma: inglés
• Títulos paralelos:
  • Aplicaciones innovadoras de las memorias morfológicas asociativas en procesamiento de imagen y reconocimiento de patrones
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• Resumen

  • Morphological Associative Memories have been proposed for some image denoising applications. They can be applied to other less restricted domains, like image retrieval and hyperspectral image unsupervised segmentation. In this paper we present these applications. In both cases the key idea is that Autoassociative Morphological Memories selective sensitivity to erosive and dilative noise can be applied to detect the morphological independence between patterns. Linear unmixing based on the sets of morphological independent patterns define a feature extraction process that is the basis for the image processing applications. We discuss some experimental results on the fish shape data base and on a synthetic hyperspectral image, including the comparison with other linear feature extraction algorithms (ICA and CCA).