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

  1. Graña Romay, Manuel
  2. Sussner, P.
  3. Ritter, G.
Revista:
Mathware & soft computing: The Magazine of the European Society for Fuzzy Logic and Technology

ISSN: 1134-5632

Año de publicación: 2003

Volumen: 10

Número: 3

Páginas: 155-168

Tipo: Artículo

Otras publicaciones en: Mathware & soft computing: The Magazine of the European Society for Fuzzy Logic and Technology

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).